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Welcome to Synopsys Investor Day. [Operator Instructions] Today's program is being recorded and webcast live. Please welcome Tushar Jain, Vice President, Synopsys Investor Relations.

Thank you. Thank you, everyone. Good afternoon, and welcome to Synopsys Investor Day. We're so glad to have you here. It's great to see so many familiar faces in person rather than on Zoom. It's a very exciting day for all of us here at Synopsys, and we thank you for joining us in person and for those joining us online.

Before I go any further, I need to read a short legal disclosure. Synopsys will discuss forecasts, targets and other forward-looking statements during today's presentation. While these statements represent our best judgment as of today, they are subject to risks and uncertainties that could cause actual results to differ materially. Important factors that may affect our future results are described in our most recent SEC filings.

We will refer to certain non-GAAP financial measures throughout today's presentation, and reconciliations to their most directly comparable GAAP financial measures can be found in the appendix section. A replay of today's event and the presentation materials will be available on our website at www.synopsys.com.

All right. With that out of the way, as I said, we have an exciting agenda lined up today. Sassine is going to cover Synopsys' next phase of growth. You're going to hear from many of our customers, and then Shankar is going to join him on stage and go deeper into our AI platform. Following that session, we'll take a short break. And then Shelagh is going to come on stage and put all of that in the context of our financial model. And we'll end the day with a Q&A session. With that, let's get started.

[Presentation]

Welcome myself. Hello, and welcome to Synopsys Investor Day. I cannot be more excited to be here in New York City with our shareholders and many who are joining us online. Before I get started, I want to send a special shout-out to our employees. I know you've been anticipating this day as much as our shareholders. And I cannot thank you enough for the trust in the strategy, the agility and courage to act and shape the future of our company and delivering with excellence. So thank you. I cannot be more humbled to be part of this company.

Now in my presentation today, I want to talk about what is changing around us and the why and how Synopsys is positioned to maximize this opportunity. This year is a special year for Synopsys. It's our 40th year anniversary. And it's very hard for companies for 40 years to start with a disruptive technology, synthesis, and maintain the leadership position, all anchored with staying on the leading edge of innovation and delivering the technology that our customers must have in order to deliver the best product that they are designing.

The other important milestone for us this year is the year 1 of the new Synopsys of the fully integrated ANSYS and Synopsys. So we're very thrilled to celebrate our 40th year anniversary as well as our new company. Over the last 40 years, we were able to deliver to our customers with different eras of technology disruption, innovation that was necessary, and we became mission-critical to our customers' success in delivering these differentiated products.

In the era of pervasive intelligence, the need to go beyond the silicon innovation to silicon to system is a necessity because the optimization cannot happen at 1 level of the stack. It has to happen at the entire stack from silicon to systems. Over the last 5 years, we've been on a mission to transform the company. 5 years ago, Art entrusted me as the President and CEO to lead the next chapter of Synopsys.

During this time, with discipline and courage, we've been able to make a number of portfolio decisions with divestitures of assets that we did not feel they were needed to deliver from silicon to system or they were not the right asset for Synopsys to hold. At the same time, we opened up our balance sheet and acquired 1 of the most essential assets for the physical AI era. And when I say physical AI, that same asset, ANSYS, is necessary to advance the chip design process as electronics and physics are merging.

When we talk about Synopsys as the leader in engineering solutions from silicon to systems, it's very rare for companies to have 3 parts of their portfolio and each part holds the #1 leadership position in its market segment. We are the #1 in EDA, in silicon IP and simulation and analysis, or as we call it, S&A. These assets are becoming critical as we envision the world, as we envision the future, the future products as digital AI and physical AI are converging.

The 1 common thing for to drive the digital AI and physical AI is advanced silicon. You're going to hear me talk repeatedly and more and more about purpose-built silicon because the world of just a generic merchant off-the-shelf silicon is not going to deliver the efficiency required and needed in order for the workload and the applications to be optimized all the way along the stack. That optimization is needed and necessary in order to drive the right cost, the right competitiveness of the product.

So when we think about silicon to system and the increased complexity, pace and cost of these designs, the need to codesign becomes a must. What does codesign mean in engineering? It means you're optimizing in 1 domain and having the adjacent domain taken into account, so you're not building too much margin in your product. And that's what Synopsys is thriving to do. That's what we call we are reengineering engineering in this era of pervasive intelligence.

How do we bring the portfolio together to enable our customers to build the most differentiated product with the lowest cost on-time, high-fidelity product with our portfolio. So when we talk about codesign and digital twinning and modeling of the end product, it's all to deliver better, faster, cheaper products for our customers. We serve a global R&D spend of $1.7 trillion. If you look at the various industries on this chart and the dollar they invest in R&D in order to build their products, this is where Synopsys opportunity comes in.

About 90% of that $1.7 trillion leans on traditional way of building a product, physical prototyping. Only 10% of that $1.7 trillion is using technology in order to build their differentiated product. The trend over the last 5 years, more money is coming towards the technology and that 10% portion of the pie is growing, just simply driven by the complexity of these products. You cannot build an EV or a robot or a drone or a chip by having a physical prototype. You need to virtualize, model, design, simulate before you build and test.

So that's the opportunity we have, and we cannot be more excited about having our strategy as AI is transforming engineering from silicon to systems and expand our opportunity. At the silicon level, more chips are required to drive this intelligence and the compute for this intelligence. These chips are increasingly becoming application optimized silicon, custom silicon. And it's evident by the number of OEM and system companies are trying to invest in building their own silicon. And the reason I'm saying trying to invest is not easy to build the most advanced silicon to support the AI and the system requirements.

At the system level, these systems are becoming more intelligent, AI-driven, a lot of software. The increased demand for simulation and analysis before you spend the money to build a physical prototype is becoming as well a necessity and more important. The physics aware codesign crosses silicon and system. On the chip level, the need to have physics simulation with electronics and physics can be fluid, structure, thermal into electronics is already happening. At the system level, having the representation of physics as your end product operating in the real world is another driver as we move into physical AI.

The 1 thing that we are very excited about is the opportunity that AI is bringing. On Monday, and Shankar will talk about it more, we announced our AI platform, where we have in multiple areas and domains an agent engineer that is able to call many of the subagents and the tools to perform tasks autonomously. And that is only possible if you can trust the results of what the agents are producing. First-time right product is essential. In order to build the first-time right product, you need a trust in physics as these agents are generating output and outcomes.

Now let's jump into the actual business. And given the tailwinds, how is Synopsys capturing these opportunities? I'll go over the EDA, S&A and design IP. And as you know, we have 2 segments. Shelagh will talk more about the segments that we have, which is design automation and design IP. I'm going to start with IP. The reason I want to start with IP, there is no better place to describe the market than our IP position.

Our IP position, when our customers are even thinking before even committing to design a chip, they come to Synopsys, and they ask about maturity readiness of a node or a foundry, about the connectivity to connect these chips together and how is the ecosystem is thinking about them. So our IP position gives us the best view of what's happening in the market. So I'm going to start with IP for that reason. What is Synopsys IP portfolio? We have what is called an interface IP, which is an IP that connects a chip to chip or chip to a system. And we have the leading position in interface IP.

We have the leadership position in foundation IP. What is a foundation IP? Think of foundation IP as the bridge between a foundry process technology to design. It's the library. When you're a foundry and you're building the next process technology, the way to represent it in design is through the foundation IP, and we have that leadership position in foundation IP. Talking about foundries, we have more than 10 foundry support in our IP business, about 80 process nodes and about 3,000-plus IP products in our portfolio.

As we think of data center, and you're hearing many of the leading silicon companies starting to position themselves as silicon to system companies. Why? Because when you think of data center, you cannot think of the chip in isolation. You have to think of the data center itself, the whole system. Now you need to take it from the data center to the rack and how to optimize and design the rack as a whole system. At the rack level, then you go to the blade. Inside the blade, there is the compute, the networking, the memory, then there you can double-click into the chip itself.

I want to spend some time on this picture right here because it's very representative of what do I mean by a general purpose merchant chip and how are our customers differentiating because the chip itself from an architecture point of view, they all look the same. You need an AI accelerator. You need a CPU. You need a memory. You need the networking, you need a bunch of interfaces to move data. Now if the architecture, you cannot be too innovative or creative with the architecture itself, where the innovation comes in is the workload down to the architecture, down to the implementation of the silicon.

So when you look at such a picture, everything you see in purple in here are our interface IP. So a big part of the system is coming from Synopsys when you're designing that advanced SoC or advanced system. The interface IP has multiple standards, and I'm going to emphasize standards. The reason those standards are important, if you are a CPU supplier and you're building your own accelerator, it's important for you as a customer to have optionality and make sure that these different components can connect together. That's where Synopsys comes in with the interface IP portfolio.

We build based on a standard, and we ensure interoperability from the host to the other part, if it's a chip-to-chip or a chip-to-system type of an integration. The reason customization is becoming very important. Many times, if you buy a merchant chip, as I'm showing you in here, sometimes the bottleneck can be the interface. That's where you're unable to move enough data. Sometimes you don't need that expensive accelerator or CPU to be idle for your specific workload. Therefore, as a system company, you're trying to optimize based on your architecture.

Now the challenge of that, the interface IP business, when I say it's been built on a standard, the traditional process for a standard, there are standard bodies. They decide what will the next UCIe, CXL, or PCIe will look like. Once the protocol definition is done, the ecosystem gets enabled, start developing, then the IP is available. That's the business we've been in now for 28 years with our IP business. Standards get defined, you build to the standard, you validate, you provide it to your customer.

The AI leaders, they are not waiting for a standard, yet they want the interoperability of a standard. They know their workload requirements, and they get started. The workload requirement define the system architecture, then they're expecting a Synopsys IP to be available way before the standard is defined. You can look at this as a massive opportunity for Synopsys or a nightmare of how to manage to deliver on a standard and customized way before the standard is defined.

Now the custom silicon opportunity, I'm sure you have your own numbers, absolutely increasing. And these are the forecast by 2030, which is 6x. The drivers are supplier optionality, cost, workload efficiency. Again, that's why our customers are building and heading towards purpose-built silicon is to address these exact challenges. Now I'm sure you follow, you see, you read, all hyperscalers are building their own silicon. And if you see the words that they're using in here, it's all about strategic flexibility and supply chain leverage. The cost of ownership from Andy, from Satya is optimizing the architecture.

So that trend, we've seen it. We've been playing in that trend. What we have -- and some of you reminded me earlier, decided to do is about 1 year ago, we said we need to adapt our business model because that's an amazing opportunity. And Synopsys is truly the enabler of all these customers and more to build their own silicon. So as customers are buying merchant, doing ASIC, building their own, that build your own silicon cannot happen without Synopsys customization of that IP.

So what we have decided to do and have been communicating in that language, Factory 1, Factory 2. Factory 1, think of it as our standard-based IP, where you wait for the standard, you build it once, you sell it many times. That's a fantastic business for Synopsys. We will continue on feeding and investing in that business because this is beyond just data center, automotive, industrial, mobile, consumer, all these chips need a standard. So the focus is not only on the data center opportunity. There's the rest of the market, which is fairly significant that requires that Factory 1 build once, sell many times.

So I don't want any confusion. We'll continue investing in this factory and leading with our IP portfolio in this factory. Then we start talking about Factory 2, where we build an application optimized IP, AoIP. An application optimized IP is we build it for a specific customer requirements. And I'll describe in a little bit more details what does that mean to build an IP in Factory 1, build an IP in Factory 2 from an engineering point of view.

The business model, the first 1, Factory 1 is you license once for a program. And if there is any NRE, we'll charge based on an NRE. In Factory 2, there's the license per program. There is customization fee, and you see here it's different than an NRE, and there's a royalty. The reason there's a customization fee and not an NRE, the scarcity of our resources needs to be put and placed on the highest opportunity as we open up Factory 2. Factory 2, the reason we can do it is the scale that we have with our IP business. We have a massive investment position in the market that is giving us the opportunity to be able to support both a Factory 1 and a Factory 2.

What's the difference from a customer engagement? And again, we'll maintain both. A Factory 1 will start with the standard being defined, the IP gets developed, the silicon gets validated with test chips, and we provide it to the customer and we licensed it broadly. In a Factory 2 model, we work with the customer very early in understanding their workloads. We become part of their system definition. Based on the workload, we codesign the IP with the customer. We'll be part of the IP integration with the customer and the system validation and production.

This is not only an IP opportunity for Synopsys. This is IP, EDA and S&A opportunity for Synopsys because as we build the IP and they're doing the system validation, we're taking into account thermal, packaging, stress, how to cool off the system. So it's an excellent opportunity to embed ourselves inside our customer workflow and deliver to this opportunity. So that's the Factory 2.

I remember as well when we talked about it, many doubters, how will you ever change a business model that's been established for 3 decades. We don't see it. We don't get it. There is no way the customer will pay for this. Do you have the skills to do it? I'm so glad and happy to report today, we have committed agreements with compute leaders, with ASIC leaders, with connectivity leaders. The press release you saw this morning is not a onetime 1 customer end of story.

Typically, back to interoperability, a system company or a leading system company, they want their ecosystem to be on the same IP. So as you're working with the system company, they pull you with their other supplier, be it an ASIC or a connectivity to ensure they are working with you, and your IP is interoperable with what they're using. This is what we released this morning. This has been a work of many, many months, not focused on the dollar and cent, focused on how you would do it inside my engineering stack. How will Synopsys team deliver with high level of confidence to my chips.

I know just in the brief few minutes, I mingled with you many questions. What's the duration? How about this? How about this? How about that? I cannot share many of the terms of this agreement, and I hope you respect that because terms of an agreement between us and a customer are confidential terms. But I can tell you the following. This is a multiyear agreement. It's a multi-generation agreement. The $1 billion that you saw, it's a license fee. Remember, there are 3 layers. There's the license fee, then there is the customization fee and then there's the royalty.

The $1 billion is a license fee for multiple generations of Graviton, Trainium and Nitro. The reason all 3 of them, because each 1 of them has a need to connect with another chip in the ecosystem. The other agreements we closed are part of that ecosystem for Amazon. We'll talk more as we wrap up this session around how meaningful that is for Synopsys and leading into the AoIP domain.

Now the other driver, including system OEMs like Amazon and other is foundry optionality. It's very important for customers, especially now more than ever before, given the shortage of supply chain, the shortage of silicon. And as you start optimizing at the system level, the system is multi-die advanced package or chiplet or 3DIC. It gives you a great opportunity to have optionality in the ecosystem. But in order to drive that optionality, you need a company like Synopsys to have the IP ready, available, tested at all the foundry -- advanced foundry leaders.

When we say we are the on-ramp to foundry, we are the on-ramp to foundry back to foundation IP, which is the bridge and the interface IP that is needed to connect the chip to chip or the chip to the system. Obviously, TSMC is the acknowledged leader in advanced process technology. This is a quote from Kevin, emphasizing the importance of Synopsys interface IP along with the foundation IP. And of course, the relationship with TSMC or any foundry is not only about IP, it's about IP and EDA enablement in order to drive that innovation moving forward.

The other questions that I've gotten from you in an intense fashion over the last year. You've lost Intel. Are you at Intel? Are you on 14A? Are you doing 18A? And remember my answer, you cannot be in the foundry business without having Synopsys IP. I don't care what others are saying. We have actually next year will be a 20th year anniversary when Synopsys and Intel got married. We became a primary partner. And the depth of the engagements, the breadth of the engagements are very well acknowledged by Intel and by Synopsys, the importance of both companies. Now I hope the video I'm about to share with you will reduce your anxiety and hopefully, the questions will be less about are you working with Intel to while we are excited about the relationship and continuation of what you started 20 years ago.

Synopsys is an important partner in Intel. We have worked together for many years across our products and foundry business from IP and EDA to simulation to analysis. For Intel 18A and Intel 18A, we are giving customers a trusted path to advanced node adoptions with silicon-proven IP, certified EDA flows and solutions based on our PDKs.

For Intel 14A, we are going deeper, co-optimizing silicon IP, AI-driven design flows and advanced packaging for the next generation of agentic and physical AI systems. AI is also changing how are designed. Synopsys is helping engineers shorten design cycles and spend more time innovating. And with ANSYS, Synopsys brings design and multiphysics sign-off closer together, which is important for advanced packaging and multi-die systems. Together, Intel and Synopsys are helping customers design better products and bring them to market faster.

Before we go to Samsung, I hope you heard the breadth from ANSYS physics to the AI portfolio to EDA to package to IP. That's the breadth and depth of the engagements we have with Intel product and Intel Foundry. The other foundry, Samsung, back to optionality and most advanced silicon is another outstanding relationship we have in the ecosystem with Samsung. Similar to Intel, similar to what we do with other foundry is how to engage early through DTCO design technology co-optimization to develop, validate the process technology, then the IP, then the IP ramp. With that, let's hear from Jinman.

Hello. I'm Jinman Han, President of Samsung Foundry. Investor Days are usually about numbers, road maps and the future. But before getting into any of that, I would simply like to say congratulations to our good friends at Synopsys on this exciting occasion. As AI continues to expand across industries from data centers and automotive to physical AI, Samsung Foundry has evolved beyond just being a wafer supplier to become a strategic partner providing comprehensive system solutions to the customers.

At the heart of this transformation, our deep IP collaboration with Synopsys Samsung Foundry has secured a robust portfolio of Synopsys IP across all processes from mainstream to leading-edge processes. More recently, to provide optimized solutions for AI applications, we have been deepening our collaboration beyond standard IP to develop customized IP. By combining Synopsys proven design IP and EDA tools with Samsung advanced process and packaging technologies, our AI platform collaboration provides end-to-end solutions that support complex custom SoC designs, including HPC and 3DIC.

This enables our customers to bring optimized products to market faster and with greater confidence across the wide range of industries. The best partnership, much like the best chips are built layer. We are proud of what Samsung and Synopsys have built together and even more excited about the many layers of innovation still ahead of us. Once again, congratulations to the entire Synopsys team. We look forward to continuing this exciting journey together. Thank you.

All right. Now to wrap up our IP section. We will be raising our long-term guide from the mid-teens to high teens for IP, driven by more design starts, AoIP expansion. This factory is firing up and accepting and ramping up on customers, the multi-foundry enablement. The projected growth for AoIP by 2030 will be $1 billion based on -- so this is a line of sight based on the current contracts and commitments that we have with customers.

The ambition is to have that business where royalty revenue is greater than the license revenue. I know a number of you asked as well, will you take a dip in your revenue as you're building up the royalty over time. Of course, royalty will ramp up over time as our customers go into production, but there is no dip. We're raising from mid-teen to high teens with AoIP factory delivering to a $1 billion by 2030 based on the current customer engagements that we have.

EDA. Now I set up the stage for IP and the need for customization, application-specific chips, et cetera. That chip cannot happen without a fast innovation in EDA. The complexity of these chips, the complexity of these systems, they need to implement whatever technology to be with or ahead of the customers as they're architecting their next system where a lot of our investment and leadership in EDA is coming in.

I'm sure you've seen many versions of this slide. If you look at the days of AlexNet or AlphaGo to Astra and the massive requirement need for the compute in order to deliver to that intelligence and reasoning, the chips that deliver to it, say, the TPU of 20 billion transistors to right now a heterogeneous multi-die system with hundreds of billions of transistors. In order for that to happen, you need EDA to lead and deliver on multiple vectors.

As you think of an advanced multi-die system, we talked about AoIP. We talked about the memory customization that is required, the whole advanced packaging requirement. Physics becomes essential. The big challenge, not architecting the system is manufacturing that system with reliability. What happens is when that system is operating in the field with the intense workloads, that system overheats, that system will fail unless you're taking all these design into account, the physics impact into account during the design stage.

Our position in EDA is truly unique. Starting from the core, the core EDA Platform, which is the leading franchise of what we call a hyperconvergent flow for the best PPA. Multiphysics fusion, this is the expansion with the ANSYS portfolio. Hardware-assisted verification is more important than ever in order to validate this complex system and will the AI workload software work when you bring that silicon back. And I don't believe the pace of innovation and shorter design cycle that we talked about in IP, which applies here, is possible without bringing more and more sophistication with AI.

Let me click through each. In the core EDA franchise, the innovation vectors are the Agentic AI automation. PPA leadership is where customers make the final decision. You cannot have a good enough performance and expect you're going to invest many hundreds of millions of dollars to manufacture the chip. You need to deliver the best power, the best performance, the best area of the chip. How to optimize the system with a multi-die advanced package.

The fusion of physics, our leadership position, #1 position with Fusion Compiler, 3DIC Compiler, PrimeTime for timing sign-off, VCS Verdi for functional simulation and debug, PrimeSim, which is a transistor level simulator. RedHawk, the industry standard sign-off for thermal. About maybe 1.5 months ago, when Jalapeno was announced, there was this simplistic extrapolation that if a model can build software, therefore, the model can build a Fusion Compiler or a PrimeSim or VCS and EDA is doomed because a model can create because all you do Synopsys is build software, the model is going to build that software.

That simplistic extrapolation cannot be more far off than reality of what customers need using the power of the model, but the essentialness of the physics and what we generate and what we sign off before you go to manufacturing is more needed than ever. Same thing, here's a quote from OpenAI, Richard Ho, who is the Head of Hardware, where he emphasized the essentialness of the Synopsys EDA in building that chip. So not only that chip did not happen through magic, there was a lot of effort in bringing EDA through the design to generate and to sign off before, in this case, handing it over to Broadcom as the back-end ASIC partner for them to implement the chip.

And Broadcom as well, long-standing relationship across the portfolio, and it was used throughout that particular chip. Now what got the attention of many is the time to design the chip. And I'll talk more about the AI contribution to the time to design the chip. But what went under the hood as a foundation to all of it is the EDA, the hardware and the IP to deliver such a system.

Multiphysics fusion, the whole thesis with ANSYS was, at some point, the monolithic chip, the scale will not necessarily hit the wall that you cannot innovate further, but you need to look at it from a system level. So the scale complexity, while it's continuing to advance node to node to node, the architecture of the system moving from a 2D to 2.5 to 3D is what kept pace in order to deliver these AI HPC chips. So both the scale and systemic complexity.

The moment you think systemic complexity, you're talking about physics challenges, stress, warpage, thermal, photonics, electromagnetics, power integrity, signal integrity. This is where Synopsys have seen this trend a decade ago. If we go back to the 2015, 2016 era, we have the complete stack. The way our customers use them is through connecting them through their own CAD and workflow. Then it moved to a fusion architecture where you start fusing engines from sign-off into design, so you have a convergent flow. You're not getting surprised later and you iterate.

In 2018, this is where our partnership with ANSYS started. We took their electromagnetic and voltage drop engine into Fusion Compiler to address that challenge. Then of course, later, as we are now integrating ANSYS and in the first wave of product releases, that technology, the multiphysics technology of ANSYS now is fused inside the digital implementation platform. There is no 1 in the EDA industry can claim this. This is unique to Synopsys. This is the differentiation of our platform. And the key is not only the design, is the multiphysics timing, power sign-off engines that are embedded and fused inside the platform.

I started with thanking you for being here and thanking our employees. When we said we're going to release the first wave of products, 9 months after closing the deal, there was a lot of doubt because it's a massive effort, massive effort. And we did release the first wave of products. And as you read what is the value, better PPA, convergence with sign-off, better outcomes. So it's better, faster, better, faster, et cetera, to achieve the outcomes that you're trying to get to.

Since then, the last earnings call, I mentioned that we have 5 customers in early deployment of the technology. It expanded to that broader list of customers since then. Why? They are seeing benefits, 10x faster photonic simulation, 3x higher fidelity for 3D geometry, and you click through it, better PPA, better turnaround time. With that, numbers are going to show that traction. In 2027, we will see revenue synergy from that first wave of integration between ANSYS and Synopsys.

Recall, we talked about $400 million synergy by 2029. Shelagh will talk in more details what is it that we'll see in '27, and how does it build our confidence toward the $400 million by 2029. Given the first wave of customer engagement and early deployment in production in '26, we know we'll be able to achieve revenue growth from that solution, which is the synergy between Synopsys and ANSYS in '27.

Hardware-assisted verification. With hardware-assisted verification, the complexity of these systems -- remember, the reason our customers, they build a customized silicon is to optimize between their software, their AI workload and the chip itself. The vehicle to do so is emulation and prototyping. You prototype the chip before the chip is there and you start running workloads. In order to do so, you need a system that has a very high capacity. Remember, those chips are massive and can run at a high speed that you can actually bring up the software and validate it.

A cool example here, actually, there is the start-up that came out of Stealth mode a few months ago. And I got many questions from investors like, hey, does this company etch, do you guys work with them? We worked with them at day 1 as they're thinking about their own company and how to build their silicon using our EDA, using our IP and how to validate it. And here, what's exciting was they were big users of our ZeBu Platform. They were able to bring up their workloads in weeks and weeks in here was about 44 days.

In 44 days after the silicon came, they were able to bring up their software. That's a process it would have took about 6, 7 months. By the time you bring the chip, you start running a lot of the software and tuning and that took 44 days. Why? Because they started in parallel. They started writing the software, validating the software before the chip was there. So that's a great example of customers using both technology together. Our portfolio span from the emulation to prototyping to what we call EP, which is a hybrid emulation prototyping system that to provide our customer flexibility.

Capacity is our differentiation. We differentiate on capacity and system-level performance. That's the use case that is the sweet spot for Synopsys. That's where we differentiate. That's why our customers buy our system, the software-defined HAV. At Converge, I explained, our customers make massive investment in dollar to buy these systems. We're innovating at the software level. So the customer does not have to refresh their hardware with every cycle. They'll buy the software that optimizes and increase the performance while maintaining the same system. That's a high, high value to our customers.

Now we monetize at the software and the actual hardware that we ship for the customer. And the need there, the demand for more and more expansion of the hardware cannot really be more insatiable that it is right now, given the complexity of the software that you're building on the chip. While I'm not announcing officially the next hardware system, but coming soon, first half of '27, the code name is Artemis. It's our next ZeBu system. And what's the expectation of the next system? Larger capacity, higher performance and a reliable and best TCO for our customers.

Now I mentioned the complexity of delivering on these chips and multiple chips in a system hasn't really been as complex and as intense as it has been now. How do we deliver to it? Our customers are looking for every opportunity possible to introduce AI into their workflow and lean on Synopsys on how to automate further because they are what you're dealing with, not only complexity, as more system companies designing chips, the scarcity of resources and people that they know how to design these chips are not readily available. With that, let me bring Shankar to go through our AI platform and strategy. Shankar?

Thank you, Sassine, and thank you all for joining us here today. I wanted to start by going back to a theme that Sassine spoke about earlier. We are in this incredible era of intelligent systems where silicon engineering and system engineering are coming together much closer than ever before. You cannot build a die without thinking about the package in which it will reside. You cannot build a package without thinking about the blade in which it will reside. And you can't build a blade without thinking about the rack in which it will design.

So this type of co-optimization that needs to happen all the way from the silicon die level design up all the way through a system-level design like a rack design is really opening up tremendous opportunities for Synopsys because of the codesign that is needed and with the portfolio we have of EDA software, our hardware solutions, our simulation and analysis solutions and our IP solutions, we believe we are uniquely positioned to deliver the silicon to systems continuum.

Now the designers of these intelligent systems are struggling with multiple challenges. The complexity of both silicon design and system design has to be tamed because it's compounding generation over generation. The speed at which these intelligent systems need to be delivered is accelerating because market windows are shrinking. We talked about building these chips and systems in 3-year cycles just a few years ago. And now we are talking about building them in 12 months with a strong desire to build them in 9 months.

And last but not least, the cost of a failure, the cost of a mistake is incredibly high because most likely you will miss a market window. So the need for getting first-time right silicon and system and software all at the same time. The stakes have never been higher. Now on top of all these challenges that design teams are facing with complexity, with cost and schedule, there's another huge challenge, which is the engineering resources needed to build these systems.

There are multiple reports that talk about the engineering shortage and a recent 1 from Goldman Sachs further highlighted this, that at the top line, the number of companies building intelligent systems, hyperscalers, system companies reaching deep into silicon design is growing, but the growth of the human capital to meet this design is not growing at the same rate. And therefore, there's a significant gap between what the human capital and capacity we have in terms of engineering and the top line resource requirements to continue this incredible build-out that we are all experiencing.

And this gap is really going to be closed by 2 things: more automation and more AI. And with the recent advances we see in agentic AI and all the frontier models, we are very confident that we now see a path of how the current human capital can apply these technologies and really meet the stringent requirements in terms of engineering resources. I want to take you through a little journey of Synopsys' AI story, which started almost 2 years ago with respect to generative AI.

At that time, models were good, but they didn't have a whole lot of reasoning capabilities. They didn't have much orchestration capabilities. And what we could do with these models essentially is build useful Copilots. With heavy context and prompt engineering, we provided useful assistance for engineers. We were able to even provide some level of automation for specific tasks, which were repetitive tasks. While these were appreciated by customers, none of this really changed the engineering workflow in any significant way and thereby did not really add significantly to the capacity of an engineering team that was trying to get more and more done with less.

But as models have evolved dramatically over the past 2 years, in terms of the ability to launch and orchestrate subagents, the ability to do extraordinary reasoning and problem solving, we are extremely excited about what the next wave of innovation is, and it's taking us towards an era of autonomous engineering. We are now able to now move to much higher level and courser level objectives where models can parse those objectives and then orchestrate a collection of agents to execute it.

And with the most recent advances in models in terms of reasoning, we are at the cusp of really enabling autonomous engineering with what we call as long horizon agents. These are agents that are able to just take a desired outcome with the necessary guardrails and the necessary constraints specified by an engineer and then able to decompose, plan and then orchestrate a very sophisticated set of tool invocations task-level agent invocations using all the proprietary knowledge assets and knowledge graphs that we have built around our tools, proprietary APIs and data we have built around into our tools and almost -- and most importantly, anchored by the ground truth engines and solvers, which are really fundamental to everything that we are doing.

So while the AI models will reason and explore, the generation of the circuits, the generation of and the validation of the designs and silicon and systems are basically done by the portfolio that we have across the silicon to system spectrum. So really, the future is long horizon agent workflows orchestrating across multiple tools and delivering outcomes, thereby ushering the era of autonomous engineering and helping us close that gap we talked about earlier.

So let me take a moment and walk you through the Synopsys Agentic AI portfolio. Because of the strength of our portfolio, as Sassine talked about earlier, all the way from silicon architecture all the way to manufacturing, TCAD, OPC and so on, and then our systems analysis portfolio, ranging from structures and fluids all the way to electromagnetics and optics, Synopsys essentially is in a unique position to deliver the broadest and deepest Agentic portfolio across engineering software.

What we are doing in every domain is delivering per domain, a set of long horizon agents that are able to take very course tasks and execute them through a complex orchestration of tools and task-level agents that are essentially able to do specific things. For example, let's take the verification domain. A verification agent engineer is able to take an outcome or an objective like here's a spec, 200, 300, 500 pages long and give me a verified RTL and test benches compared to the spec. Or here is a design that I'm trying to improve the coverage on and I have about 30%, 40% coverage, take this and make this into a 90% coverage situation.

An implementation agent engineer is now able to specify an outcome like here's a collection of blocks that I want you to run an autonomous place and route closure, run sign-off, do the ECOs after sign-off and essentially close this block for me. That's an example of a long horizon agent in implementation. Moving to analog design. The nature of the task is no longer let me click these 10 buttons to get this transistor moved from point A to point B or to connect this device to this other device. The nature of the task is, here is a spec of a circuit that I want to build, go through the design of the schematic, the layout and the simulation of that resulting design and meet these objectives.

That's what we mean by long horizon agents. And these agents are essentially invoking a strong library of task level agents provided by Synopsys per domain. And of course, everything is anchored by the ground truth physics solvers and engines that we have built across decades across the entire spectrum of silicon to systems. The story doesn't end just in silicon. We've also now extended the same philosophy over to simulation and analysis.

So a CFD engineer can essentially provide a geometry, describe the kind of objectives that they are looking for and the entire setup and meshing of the CFD, the execution of Fluent and then the results analysis of the Fluent CFD simulation and then the next steps in order to further improve that all gets handled by a long horizon agent. So this is really something that we believe is going to bring a significant level of autonomy into engineering workflows and thereby increase the capacity.

Now all these capabilities, the long horizon agents, the task agents that the long horizon agents can invoke and then all the invocation of the tools are all driven by the Synopsys Agentic AI platform, which we call Autopilot. It is the broadest and deepest portfolio, as I mentioned, across the entire engineering spectrum from silicon to systems. And so a couple of things that are unique about this platform. First and foremost, interoperability and openness.

In this platform, our customers can onboard their agents to benefit from all the assets on the platform like our knowledge graphs, proprietary APIs, proprietary data to write powerful agents on our platform. At the same time, we want to meet our customers where they are at. And so if they are down their agentic journey and they want to integrate our agents into their agentic workflow, we also connect to our customers' agentic environments through protocols like MCP and A2A to essentially enable that as well.

Last but not least, the compute and LLM optionality. It is -- essentially, today, we are supporting the entire spectrum of proprietary foundation models all the way through open source foundation models. And really, the performance of the agentic capability regardless of domain is heavily dependent on the quality of the foundation model and the ability of reasoning that it's able to do, the ability of orchestration it's able to do. And as you will hear later, there's a tremendous opportunity here as well in terms of how to really work with foundation models that understand semiconductors or physics much better and thereby get even better results.

So a picture conveys a thousand words, but I believe a demo conveys 100,000 words. So let me give you an example of how our 3DIC agent engineer is able to go from a very core spec of what an AI advanced package looks like, almost a napkin diagram and take that and work through the entire process of advanced package design and simulation. This is an area which transcends multiple domains, the design, which is now anchored in Synopsys 3DIC Compiler, all the multiphysics analysis steps that are anchored in the ANSYS technologies of HFSS and RedHawk and many others. And what you will see here is how the long Horizon agent is able to decompose the objective and execute task agents, execute the ground truth tools at the base of it and really run an end-to-end flow to design an advanced 3DIC. So if you could please.

[Presentation]

I hope you can see why we are so excited about how these long horizon agent engineers can really change the way in which engineering is being done and really increased capacity in very stretched engineering teams. Let me now give you an example from the simulation and analysis area. And here, we are going to look at electromagnetic coupling and electromagnetic interference, which is very important for any electronics design.

And what you're going to see here essentially is how an engineer essentially is using the Synopsys Agentic Autopilot Platform to really execute an EM analysis of a design, find specific signals where they think there might be problems, do some sweeps, simulation sweeps to determine whether or not the simulation results are meeting some industry standard requirements, which is encoded in something called a CISPR 22. So let's take a look at ANSYS HFSS and ANSYS Electronics Desktop embedded within the Synopsys Autopilot Platform and enabling an agent engineer flow.

So here, what you can see is look at the objective that has been provided here. And again, it's all natural language interface, right? There's no clicking of buttons and no pulling down menus. And essentially, the directive was given to run the EMI scanner on this PCB and then the necessary tools are getting set up and invoked. The results from those tools are being summarized, analyzed. And now the engineer says zoom into the clock net because I think that's where the problem is. And again, the right tool level invocations are happening underneath.

And then the next query is, hey, do me a sweep across a range of frequencies and show me what the fields look like. And again, this is what I mean by specifying outcomes and objectives rather than having to know the intricacies of the tool and how to drive the tool to get specific results. And in this case, you see the radiated emissions. And then the next request here is plot the SIwave results and then compare it to CISPR 22, which is a standard for EM interference.

And again, here, it's basically opening up the CISPR 22 PDF, understanding what the requirements are, firing a plot, taking these results and essentially generating the comparison to the CISPR 22 standards, which is basically illustrated by -- and in fact, it doesn't find the file, it goes and locates it correctly. And then it basically plots the final graph comparing the field values from the EM simulation against what the guidelines are with respect to the standards.

So this is kind of really illustrating how the nature of design is changing with agentic AI and how -- in this case, the red line is the CISPR 22 requirements, and you can see the plot is basically satisfying those requirements. And so natural language interfaces, all the tool calling is being handled by the agents. The proprietary knowledge and the skills that Synopsys has built up over decades is all encoded into the platform. And this is how we are really kind of revolutionizing the way in which agentic AI interconnects with the engineering.

Now 1 key point to touch upon is really what is happening underneath in terms of the tool calling. So let's take an example of a verification team in a hardware design group, and they've been handed a spec, and they have to write the test plan and the tests corresponding to that spec in parallel to the design team implementing the design. So in the typical setup, there's a lead who takes that spec breaks it up across their team of verification engineers, assigns each of them a portion of the spec and then they then go off essentially running our verification tools like VCS or debug tools like Verdi and essentially building those tests.

But all that work that is being done is essentially gated by things like, hey, I've got meetings all day today or I don't work necessarily all weekends. I don't work late into the evening. So to a certain extent, the total work that can be accomplished is gated by the amount of human cycles that are available. Contrast that now with an agent engineer, a long horizon agent engineer that has now handed that same spec and essentially with the right knowledge graphs from Synopsys embedded within the Synopsys Autopilot Platform and all the task agents available, there's a rapid decomposition of that spec.

And essentially, agents are fired off to work on different parts of the spec. And beyond just writing tests, these agents can also explore a much larger solution space to write high-quality tests. And so as a result, when you look at the tool license, the tool profiles and the tool calling profiles, essentially, we see -- we have an expectation of a much higher tool calling profile than in the case where we don't have agent engineers because you're only gated by the compute on the right-hand side.

The more compute you have, the more exploration, the more agents that can run in parallel and as a result, finish this task with high quality and much, much faster and essentially expand the capacity of this team. So that's really why we believe that the move to agentic AI and agentic execution is going to significantly increase the tool usage. Let me finally conclude with the momentum that we have with our portfolio across the industry, right? Over 50 engagements with all the top customers, and many of them are now seeing the value of the agent engineers and the Agentic platform that we have delivered.

For example, Intel is seeing a lot of value in the work we are doing with them on reducing their verification bottlenecks and improving the engineering efficiency of their design and verification teams. MediaTek, we are working with them very closely on something which is a very, very laborious design step, analog and mixed-signal design. And here, MediaTek is engaging with Synopsys to essentially take our Agent analog design capabilities and essentially use agent engineers to achieve significant productivity benefit in the design verification as well as optimization of analog circuits.

Samsung Memory is also working with us very closely to use our Agentic portfolio to accelerate their engineering processes and design steps for high-bandwidth memory design and DRAM design and again, very close collaboration there. And then NVIDIA is both a partner as well as a customer. So of course, as a partner, we work together very closely on the Agentic platform and many of the components in our platform. We kind of codevelop it with NVIDIA. But then they are also a consumer of all the agent engineers and the agents that we are delivering through the Autopilot platform, and they're also seeing tremendous benefit and value from all the innovations that we are driving. So with that, let me hand it back to Sassine to now talk about the AI monetization. Thank you.

All right. What you heard from Shankar and the snippet from Richard at OpenAI, I hope I don't have to convince you that AI is absolutely a TAM expansion for EDA. You need the essentialness of EDA to generate, to validate. And therefore, we expect our tool usage will only expand with the combination of a human and agent engineers. I have been over the last 5, 6 months describing that our customers will not apply AI in the same way across multiple customers. Customers try to differentiate in the way they're going to implement and evolve their workflow.

Therefore, Synopsys' strategy is to provide a solution that adapts to the various customer flavors of adopting AI. Let me walk through the various choices that we have and can offer customers. The Synopsys full stack, that's what Shankar just described, where the customer can come to Synopsys, they get the platform, the agents, the tools and they provide objectives to AI and to achieve a certain outcome. This is a significant investment we've been making. We'll continue on leading and put our resources, energy effort in the Synopsys full stack.

The second choice customers are making, and there are a lot of customers, by the way, in that second category, where they're saying, I have my own special sauce. I want to build my own agent. I want to build my own platform. What I need from you, Synopsys is access to your tools and access to some of your agents. I don't want to reinvent a debug agent. I'll get the debug agent from you, Synopsys, but I want to own the rest of my platform for various very good reasons.

The third model or choice is a frontier model. As you have seen, and we have discussed it many times, when you have a model that comes out 1 day and say, I was able to perform this specific task in semiconductor chip design. In many cases, those models were using open source because that's what they have available. And they saw good either productivity or proof of concept. With the advancement in frontier intelligence and reasoning, I have no doubt that there will be a convergence with frontier models with EDA in order to achieve the best outcome as another customer choice.

Across all choices, EDA and S&A engines are essential as the physics-based ground truth. You will not tape out a chip if you're not going through the sign-off gates in order to ensure that whatever has been explored, proposed by AI is being validated. Now let me walk you through quickly how are we thinking in terms of monetization. We talked about subscription and consumption in the last couple of earnings calls. In the Synopsys full stack, the customer can subscribe through subscription license to the Synopsys Platform and to the Synopsys agents, as well as the Synopsys tools.

Now Shankar showed 5 to 10x more consumption sometimes the agent can trigger. In a number of cases, the customers, they may choose to have a subscription for the tool and a consumption based. The consumption can be on-prem, cloud, we have it available whatever customer choice they choose. So that's the monetization stack using the Synopsys stack. The second revenue stream is when the customers are saying, I may want to have a hybrid, I want to license some of your agents, and I need your tools to build my agents or your tools to run your agents because it's going to consume more licenses. We'll have the agent subscription that sits inside the customer platform and the tool subscription and consumption.

The third, when you're training a model, you need tools to train it. So that's a tool subscription. When you're inferencing the model, you need tools to run it. So that's a subscription and consumption. And then there's a revenue share. A lot of the questions will come up, how and based on what will you have revenue share is going to be based on outcome. If you're able to achieve a certain PPA with the best optimized RTL that you created, but the model, given it can explore much broader, can provide a better PPA. Will that better PPA be worth x dollar and therefore, what's the revenue share model in this use case.

Now here, we've been working for actually right now many months, close to 2 quarters, assessing who, how, what's the model to protect Synopsys IP if the model is trained on Synopsys because when a model is trained on open source is 1 way. When it's trained on Synopsys, what is the role of Synopsys in training that model in inferencing the model, who owns go-to-market, who owns the monetization process. So as we've gone through many of these iterations and talking and collaborating with many of the AI labs, I'm very pleased to announce today a partnership multiyear with Synopsys and OpenAI.

And the cool thing about it, there will be a specialized GPT-Synopsys model where it's posttrained using Synopsys agents, tools, skills and workflows. So we bring in the knowledge with our tools, with our workflow and skills. OpenAI brings in their frontier intelligence and reasoning and the combination of both should provide the best outcome period in terms of -- as measured by an objective. As Shankar showed in the demo, you can provide at the PPA objective, certain targets, et cetera. So this multiyear arrangement is available now to a set of customers that are in early engagements to see what is the outcome of a model converge with the best-in-class EDA versus an open source or other alternatives EDA. Before I go into more details, actually, let's hear from Greg at OpenAI.

Hi, everyone. I'm Greg Brockman from OpenAI. We're really excited to be partnering with Synopsys to accelerate chip design for everyone. At OpenAI, our progress in AI depends fundamentally on the chips that we run on, and now we have an opportunity to use AI to help design those chips. Synopsys brings deep engineering expertise and the tools that chip designers already rely on. And together, we're building a specialized AI model that is built specifically to master these tools.

The goal is to bring together Frontier intelligence with the ability to use Synopsys EDA tools. And this will help engineers autonomously explore a much greater range of design choices to efficiently trade design targets and to get to a working chip faster to be able to shave off weeks, months from the design process and to bring more chips to the world. And what I find really exciting is that this is something we can build on itself. Better AI helps engineers design better chips. Better chips makes AI more capable, more efficient, more accessible to everyone to empower people around the world. That is something that our work together will help accelerate. So thank you, Sassine. Thank you to the whole Synopsys team. We're excited to build this with you and to see what your customers will achieve.

All right. This is actually very, very exciting options for customers as they're assessing how much do they invest in their own intelligence models, workflows, the Synopsys full stack and the OpenAI Synopsys option. I know most likely you have a lot of questions on your mind. And I did not give you much runway on this 1 like we did this morning with IP. So we'll take the questions later. But just to give you some color, the key things to emphasize, this is a specialized model. It's a GPT-Synopsys, meaning whatever learning that goes into the model, it stays Synopsys proprietary inside that model. So our IP does not leak or disappear into the bigger base model.

The objective is to optimize, verify, deliver best outcome. So you give it objectives, you deliver outcome. And there are engagements underway. Let me add a little bit more color. How will customers access this? Think of it as a service. A customer will go to Synopsys go-to-market or Synopsys go-to-market goes to the customer. And they can or an OpenAI directly with the customer. The customer will go to OpenAI. They get access to the model, GPT Synopsys. They get access to the compute. They get access to the EDA tools, agents. And through that engagement, it will be an outcome-based.

And that's where we monetize back on the prior slide I showed you, the subscription of training the model, the subscription/consumption and the value -- the revenue share component. I cannot be more thrilled for EDA that we'll be able to capture value based on the high impact we deliver to our customers as yet another option in this era where AI is making significant progress in intelligence and reasoning. If I were to summarize, AI for EDA, is it a tailwind or a headwind?

The key concepts that we all need to be very clear on what AI can do, AI can reason and explore. You need EDA when that intelligent model is providing a task or guiding, you need EDA to generate. You need EDA to generate a GDS, a layout, a clock, et cetera, et cetera. And you need EDA to validate. So there is AI can explore, can recommend, but you need Synopsys to generate and validate. Agentic AI will reason, orchestrate, execute. Synopsys ground truth engines are a must because they are foundry-certified sign-off back to we're the bridge for DTCO, we're the bridge to foundry.

They're deterministic. They're physics grounded. And we've gone through the rigorous validation and manufacturing and yield assurances. That's what our industry and Synopsys has led and done over decades. So when you think of an intelligent model, frontier model, that's a huge value, fantastic value to do the exploration, et cetera, with EDA to bring the high impact. And of course, the outcome will be a verified outcome. I'm not sure if you've noticed the sentence in quote. If I were to summarize what customers tells us all the time, and you see it consistently, can be summarized here. In AI, we believe, but in physics, we trust.

Customers are not saying, I'm not sure if AI, I'm going to adopt it or not. They are adopting AI. At the same time, they need physics to validate. They need sign-off to validate. From an EDA growth, we talked about the synergy of electronics and physics. More design start and AI-driven chip design, we are raising our long-term guide from double-digit to mid-teens growth. We talked about it will be -- '27 will be the year where we will see the revenue synergy from the ANSYS acquisition. We will see revenue from AI, and we will see continued acceleration in EDA as well as HAV, the hardware-assisted verification.

Let me next go to S&A, but let me introduce the S&A section actually with a short video. It's always cooler to have S&A videos versus chip videos. Chip videos, they seem so boring. S&A, you can look at the car, the airplane, the data center between electronics, et cetera. So that's a great video actually of codesign. Codesign of electronics with the whole rack, the structure of the data center, the cooling, et cetera. So what are the complexity of intelligent system design? The failures that are caught late are so costly and it takes so much time.

But the trade-off companies need to make. If I do a lot of modeling and simulation upfront, I need certain skills. I need to change my workflow. It's hard to do it. And companies, customers, they don't innovate unless the constraints are high. And when the constraints are high, can be driven that those systems are becoming more intelligent. Those systems to serve need to serve various different applications that is necessary to bring in a different workflow for these systems. So today, with our S&A portfolio, we pretty much serve every 1 of these markets.

The ANSYS acquisition expanded the Synopsys customer base by 10x, 10x expansion of our customer base. Now the beauty, many of those customers are looking for the next method of designing these intelligent systems. Now if they're building their chips and expanding to build their chips, that's fantastic. That's even a bigger opportunity for Synopsys. If they're sourcing the chip, but they're looking for a new way to improve from a traditional development model, which historically until now back to that 90% of the $1.7 trillion is done through this traditional model where you may have -- you have requirement, you design, you may or may not simulate, you build, you test.

Then if you find failure, you go back through the loop of testing, then redesigning and building. The simulation usage is fairly limited by few inside these companies that called analysts that after the design is done, it goes through a different group to do some simulation as the product is being built and tested. Now the opportunity is how do we make simulation more accessible, where the simulation is done during the design and more and more simulation is, again, accessible before the product goes into build and testing.

Now that concept is not new to many companies that they are building the intelligent systems and they need and have to deliver these products on time. This is a set of customers are of many that have adopted early the simulation in the new way of building a product. And you can see what they see is a closer correlation to an actual physical testing without -- while reducing the need for as much physical testing. Now what Synopsys has with our S&A portfolio is the multiphysics trust and sign-off. And that's very important because you can simulate all day long. If you don't have fidelity in that simulation, you will not use it.

So ANSYS and our S&A portfolio across 5 physics, fluid dynamics, structure, electromagnetics, optical and thermal, we have the leadership position. It is the ground truth of sign-off for the physics domains. AI is not only impacting EDA. It's the same thing for S&A. The democratization of simulation has been a long multiyear effort to bring simulation from few analysts to a broader set of users of simulation. The next set or opportunity is AI-driven surrogate models. We have technology called SimAI and optiSLang.

What SimAI does is you can upload a prior simulation data from the prior design and can predict and gives you through optiSLang options of design. If you were to change the curvature of a blade in a jet engine or in a car or in a robot, how does it change the performance of the product you're building? So you can get it done through surrogate models in a fraction of the time, then you do the final simulation for sign-off. So it's an opportunity to do a different type of simulation faster through models and which is the surrogate model opportunity.

Shankar talked about the agent engineer for physics. This is an investment immediately when we closed the acquisition, we brought the ANSYS R&D to operate into the same platform rhythm strategy around AI and the agent engineering. And as Shankar mentioned, we have the first wave of customer engagements and announcements there with agents. With Frontier models, the same as I just announced with OpenAI for semiconductor. I see it as a potential for systems, not only for silicon for systems as well. And the opportunity is very similar. Can you leverage frontier models with the ground truth physics to explore, simulate, test physical AI products.

Shankar already went through this. The platform, the Synopsys Autopilot Platform with domain-specific agents expand into physics, and that provides Synopsys the opportunity to have an AI-powered simulation across multiple domains and multiple industries. That's the simulation aspect of it. You recall about 1 year ago, we announced the partnership with NVIDIA, where we will leverage the Omniverse from NVIDIA and Synopsys simulation and analysis across various industries where Omniverse provides the customer the ability to envision, visualize their product, design their product and Synopsys' engines are used to simulate because, again, they have the ground truth sign-off of physics.

We have many customer engagements there. And actually, it was very cool earlier this week to see AMD buying World Labs. It's the same approach. Why? Those intelligent systems, you need a digital twin of electronics. You need digital twins of the physics. You need a digital twin of the environment in which that system is operating. If it's a data center, it's data center, it's a car, it's the world environment, et cetera. So the direction we took with NVIDIA Omniverse is a validation earlier this week that, that's a market that is expanding. And there will be similar type of collaboration that we expand as, of course, the acquisition will close, et cetera, et cetera.

To summarize, for S&A, the long-term double-digit growth, that's organic, and that's higher than the traditional growth that ANSYS as a stand-alone organic has been able to achieve and is driven by a number of tailwinds. More simulation are needed, more value capture through accelerated simulation. This is a GPU acceleration and other. The AI-driven inflection point we just talked about and the new opportunities through digital twin and other.

Now to bring things to close and summarize, the long-term growth outlook is mid-teens CAGR through 2030. If you recall, that used to be double digits, and the reason it's mid-teens is the growth we've talked about for EDA, mid-teens, IP, high teens and S&A, the double digits. FY '27 outlook at 15% year-over-year growth. Some of you asked me earlier, how much did you prep for this meeting? I'm like actually, the meeting itself, it was less the prep. The prep was the FY '27, we pulled by 2.5 months to provide you the FY '27 and not miss the opportunity to be here and share with you our enthusiasm, our excitement, what is driving it and of course, some of the major collaboration and redefining some of the businesses that we have.

Just to summarize, this is our opportunity. At the silicon level, the expansion of application optimized silicon gave us the opportunity to create a new category of IP, which is AoIP anchored with a license fee and a royalty, which is a significant opportunity for Synopsys. AI for EDA, along with everything that we do in terms of multiphysics fusion, the entire platform, HAV, et cetera, the open AI option for customers as well as the customer choice of building and mixing their agents or a full stack from Synopsys, that will all contribute to our growth in '27 and will only expand beyond '27.

Systems, more S&A is needed for these intelligent systems and truly what differentiates our assets and company is the ground truth, highly trusted physics that we do in both silicon and systems. With that, big, big thank you. Now we'll take a break, and I look forward for the Q&As. Thank you.

We will now take a short break. Please return to your seats in 15 minutes.

[Break]

Please welcome Shelagh Glaser, Chief Financial Officer.

Thank you. It's great to see everybody. Thank you so much for coming. I know there's a lot going on. So thanks for prioritizing time with us. I'm going to bring together everything you've heard today and show how it comes together in the financial model for the company. But first, Sassine talked about this being a major inflection point in the industry. And why is this moment different? The complexity and the pace that is happening in system and silicon design has never been faster. But there's a talent gap in a compute gap. So AI is going to help bridge the gap on that.

And customers are increasingly designing integrated physical and digital systems, which require codesign. Shankar went into a lot of detail about that. And first-time right economics have never been more important to customers. Having to do another spin or another tape out is hundreds of millions of dollars of a new tape-out, but even more importantly, it's missing a market window. So that's missing revenue. When customers have to overdesign, that leads to bloated die sizes, which leads to yield problems, which leads to less units to be able to sell.

And so customers need to come to us because we're uniquely positioned with the leadership portfolio in EDA, in S&A and IP so that they can be confident that they have the ground truth physics and sign-off. So the models they build of the products are going to be the same as what they're going to see in high-volume manufacture. We're the link that allows them to have that confidence. And we have traditionally been seen as we're solving R&D problems.

But as Shankar and Sassine laid out we are driving even more value for customers. The problems we're solving are making sure that they're able to hit their revenue targets, their chips are on time. They're hitting the right PPA margin targets, they're achieving the yield and the cost that they want. We're making sure they have time to market and high confidence product schedules and high-confidence product success as they move from doing designs and models into actually taking those products into high-volume manufacture. So this is the early innings of increased value capture that Sassine laid out and the change in our business models that we are driving. And we are in the early innings, and this will build over time.

Let me take a step back and talk about where we've been. Over the last 5 years, we've doubled the size of revenue of the company. Over that same period of time, we have driven significant margin expansion, 7-plus points and margin expansion. And we did that while integrating 1 of the largest acquisitions in the software industry and the largest acquisition our company has ever done.

So we've proven that we can grow both scale and we can grow profitability. And in 2016, this has been a year of execution for us. It's our first full year, as Sistine said, bringing ANSYS in over the course of the year from our initial guide, we've raised outlook on all key metrics. We've raised outlook on revenue, non-GAAP operating margin, non-GAAP EPS and free cash flow.

And importantly, this momentum has been broad-based across all of our businesses, and we've been translating more profitability into more cash versus disciplined execution. This helps set the stage for the next era of growth for us as a company. Before I go into the long-term model, I want to make it clear how we will present the company starting in fiscal 2027. We'll continue to have the same segments, design Imation and design IP. What we will change is the revenue disaggregation.

Specifically, what we committed to this year was to provide full transparency on ANSYS our first year of this consequential acquisition, and we've delivered on that. As we move forward and we build out this multi fusion physics product lines, it will be harder to separate ANSYS and EDA products. So what we will be presenting in fiscal year 2027, we'll move the semiconductor business unit from ANSYS into that's about 10% through Q3 '26 of the revenue of ANSYS. We will also use that remainder advances and show that to you in simulation and analysis.

Design IP will remain unchanged. These changes align to how the industry views these and it will allow us to give you full transparency of the performance on our EDA business and our simulation and analysis business. And throughout the course of the year, we'll provide apples-to-apples comparison because obviously, we'll have the comparison with '26 how we report it.

Now let me get into the growth algorithm. And Sassine laid this out in his section, for this year, for '26, we anticipate revenue of $9.7 billion, and as we are driving to fiscal year 2030, we are driving to a model of mid-teens overall growth Underpinning that is mid-teens growth for EDA with a floor of 13%, double-digit S&A growth with a floor of 10% and design IP with a floor of 17%.

This is all underpinned by what Sassine talked about in terms of increasing design starts, increasing complexity, increasing need to do co-optimization, and in the design IP, Sassine laid out the new business model that we're driving with application optimized IP. Underpinning this is revenue synergies, which I'll talk about in a minute, and increased value capture as we evolve our monetization model and change the way that we work with customers on that.

Let me go into synergies. So when we announced the ANSYS acquisition in January 24, we committed to both revenue and cost synergies, and I want to provide an update on both of those.

So let's start with revenue synergies. On revenue synergies, the commitment is $400 million run rate and synergies by fiscal year 2029. What we have already done, which we talked about today, Sassine laid out again today, is we've already built a new joint road map, the multiphysics fusion products, we're seeing great customer enthusiasm on that, and those will start to revenue in 2027.

We've also brought the sales teams together so the sales teams can have cross-selling really across the entire product line. As we exit fiscal year 2027, we will have greater than $100 million run rate in revenue synergies. So the synergies begin in earnest in 2027, and we have confidence in our ability to achieve the $400 million run rate synergies by 2029.

Now let's talk about cost synergies. On cost synergies, we had committed to $400 million run rate by fiscal year 2028. As we've talked in each of the earnings calls throughout this year in fiscal year 2026, we've been accelerating those synergies, and I'm pleased to announce today that we will be complete with our $400 million run rate synergies in fiscal year 2027, which will be 1 year early. So we are executing against our synergies and feeling very confident in our ability to achieve these.

What we done with cost in 2027 and we've got strong line of sight to 2029, given the strength of the first year of revenue synergies we'll have in 2027. Now let's talk about operating margin. So Sassine laid out the change we're driving in the business model. That change flows into operating margin. So I'm pleased to say that our objective in operating margin is approximately 50% by fiscal year 2030. That's up from our prior expectation of mid-40s, and it's driven by the changes in the business model that Sassine outlined.

And how we're doing that is on multiple levels. So we're scaling and bringing efficiency into everything in the business. In the scaling, we're working on higher value capture that Sassine outlined today as we have evolved the business model and IP, and we infuse AI into our products. Portfolio optimization that's something you've seen us do year after year, making sure that we've got our investments in the highest return areas, and that's a constant evaluation that we do and then operating leverage in everything we do.

Literally, how do we simplify every process and every approach in the company so we move friction, so we focus on high value add. While we're doing that, it isn't about cost cutting. It's about efficiency and leverage and investing in critical innovation, which fuels the strategy that Sassine laid out. Specifically, large areas of investment we're making is advanced node and multi-die design to be able to support our customers as they endeavor on these more and more complex designs.

Making sure that we're building innovation and simulation and digital engineering to be able to make sure that we're supporting those customers and infusing AI for engineering and all that we do.

So just as we're working with our customers to infuse AI, we're infusing it so that our team gets the benefit of that and funding the application optimized IP formerly called Factory 2 in IP. So building that out. We're not -- we're keeping both factories. Sassine talked about the Factory 1, which is our traditional IP. So we're keeping that, and we're adding on top of that investment to build out this new model. Then let's talk about the capital allocation framework.

Our priorities are clear. Our priority, first and foremost, is to invest in growth in the business and invest in R&D that fuels the innovation that drives the business. And on a regular basis to make sure that we've got the investment in the right areas to drive the growth of the company. We will drive selective and disciplined M&A. The second is to maintain a strong balance sheet and maintain investment-grade rating. You've seen us pay off the term loans early as an important part of our operating plan as we drove through this past year to get the term loans paid down.

And the third is to regularly return capital to our shareholders. And here, we will return up to 50% of free cash flow to shareholders. And so this framework allows us to invest for growth, to build the innovation that fuels the strategy while creating shareholder value. Another thing that we've talked about, many of us have talked about is how we think about stock-based compensation. So we are targeting 8% SBC as a percent of revenue by fiscal year 2030. We will do this through revenue growth and scale and disciplined application of our equity program.

You've already seen us make significant progress on this. We are down 3% from our peak in 2025 of approximately 13%. And like our investment dollars, we think in a very disciplined way about where we put our equity. And this allows us to ensure that we're investing in attracting and retaining top talent, which is absolutely necessary to ensure that we're building the innovation out and building the capabilities that will allow us to achieve our strategy.

Now all of this will compound in both EPS and free cash flow. So with revenue growing in the mid-teens, operating margin scaling to approximately 15% and we will grow EPS and free cash in the mid-20s. This is a durable compounding growth plan that translates into profits and shows up in cash.

So putting it all together, these are our long-term financial objectives. It's underpinned by three scaled market-leading businesses and the change that we're driving in the business model with AI and the application optimized IP and underpinned by our synergies realization. We're not dependent on any one single variable. We have multiple growth vectors that we're driving. And what we're driving is both growth and leverage, which shows up in EPS and free cash flow growing even faster. And we're doing all of this while we're investing to ensure that we can continue to fuel the growth and returning capital to shareholders.

Now let's zoom into 2027. And as Sassine mentioned, we're giving our full 2027 guide today, which we would normally give in December. But since we're together, we thought it was very important that we talk about what does '27 look like. And so let's shift into that. So '27 is a very important validation year of this long-term model that we're laying out today. We expect to grow revenue 15% to $11.15 billion to expand operating margin 250 basis points to 44% and to grow EPS even faster at '27 to $19.08.

All of these numbers are obviously at the midpoint. This represents the strength of our underlying business and it's a great start towards the long-term model that we've laid out today. And I want to talk a little bit on operating margin because this has been a question for quite some time. So I'm sure we're really clear on this. So what we've talked about in 26 is our expectation for full year '26 is 41.5%.

So that's 420 basis points improvement from fiscal year 2025. On top of that, what I just guided for 27 is another 250 basis points improvement. And again, we'll have the full realization of synergies next year, and we're driving the greater scale in the business while we're continuing to invest in the business and continuing to invest in important strategic objectives to achieve the product lines that will help our customers scale.

Putting it all together, our guidance for 2027 is extremely strong. We're very confident in this. This is why we feel comfortable giving this to you in September instead of waiting for December. You've seen us accelerate into the second half of 2026. You've heard the new deals announced today. And so we have strong progress towards these long-term goals, and '27 is an important year to be able to demonstrate that. On top of the metrics, I already talked about free cash flow will be approximately $3.1 billion, and that's up about $0.5 billion year-on-year.

Just one more thing before we get into Q&A. Given the strength of the balance sheet and our business model, we are announcing our intent to repurchase $1 billion in Synopsys shares over the coming months. This is based on our confidence in the model and our cash generation, and it aligns exactly with the capital priorities I just outlined. Number one, to invest in our business, number two, to ensure we have a strong balance sheet; and number three, to make sure we're returning capital to shareholders. This allows us to offset dilution and over time, the repurchase program will allow us to reduce share count.

So let me sum up. We are at an industry inflection point. Complexity is outpacing engineering capacity. First-time right is absolutely high stakes for our customers. People cannot -- customers cannot afford to miss critical market windows. We have the portfolio that allows them to have high confidence in being able to ensure that they're building products that will achieve their goals and will be right the first time.

Our financial goals are mid-teens revenue growth with margin expansion and free cash flow expansion. We're confident in our execution, and we're confident in our value creation. And the first step towards this long-term model is our fiscal year 2027 guide. With that, thanks. And we're going to move into Q&A.

Please welcome back Sassine Ghazi, President and CEO; and Shelagh Glaser, CFO.

So I'm going to -- we're going to have two mic runners, Chris and Christine, and they will come to you guys. And then I'll -- you can ask your question, please state your name and the firm. I ask you to limit yourself to one question, and then I can come back to you guys if you have more questions. So we'll begin with Siti.

Sitikantha Panigrahi from Mizuho, First of all, congratulations as an amazing Investor's Day. And thanks to Tushar, Tushar and his team has put together a really good Investor's Day, and thanks for inviting us. Sassine, as you say guide, not only '27, even your long-term guidance, it's amazing much better than we're expecting. The question is, when you laid out a lot of growth opportunity, which -- how do you rank order and what gives you that confidence to hit that number?

And specifically, on the AI opportunity, I would like to ask the difference scenarios areas you just talked about. Where do you -- who owns that value capture part, which scenario you have higher value capture versus other models?

Yes. Thank you for the question. We will not talk about 15% unless we have confidence we're going to meet the 15%, and it's really the layers that we described, starting with IP the -- even though the royalty will not show up in '27. But starting in '28 and then it starts ramping into '29 and beyond, that becomes a fairly large percentage of our IP business that comes through royalty.

And while Factory 1 will continue on executing and delivering to the double-digit expectation as well. So all in all, in IP, as Shelagh mentioned, the floor is the 17% with an objective to grow in the high teens. And EDA is the same. I want to remind us that the floor is with the objective for mid-teens. The EDA between synergy of the multiphysics. AI definitely will start contributing in FY '27 and the -- I want to call it the classic EDA growth of delivering to just the best-in-class software and hardware in order to achieve these opportunities. In terms of AI for EDA, we talked about 3 revenue streams.

Revenue stream one, the investment is essential because those agents, if the customer subscribing to them either an option 1 or 2, that investment and delivering to these agents is essential to have that capability differentiated capability. It's clear for our customers how to pay synopsis in stream 1 and stream 2 because they know they need to subscribe for the platform, the agent and the license or some consumption of the license. We already have a number of customer engagements.

That's what gives us the confidence in '27, we will see revenue from Stream 1 and 2. Stream 3, the revenue share, we are currently in number of customer engagements, testing the GPT-Synopsys based on outcome. So you give it an objective if the outcome is better than what they're able to achieve, the monetization will happen based on what I call the service. So because that model runs on OpenAI cloud, so they provide the model the compute.

So the customer gets a model, compute, EDA licenses, EDA agents and the harnesses, the context, the skills that are required. And then there's a revenue share split between us and OpenAI to -- based on these outcomes. So that's a whole new stream of revenue that we were not able to capture before. So that's a new revenue stream that we're looking at. That's why the mid-teens for EDA with a floor of 13% starting in '27 is something that we're confident about delivering.

We'll go with Jim at Goldman.

Jim Schneider, Goldman Sachs. Congratulations on the targets. I was wondering if you can maybe talk a little bit about, given the accelerating growth rates you're expecting across the businesses, to what extent is pricing and pricing to value sort of driving or underpinning those targets? And can you maybe talk about any like-for-like pricing conversations you're having with customers to sort of drive that accelerating growth? Or is that purely on the basis of either mix or top line benefits from elsewhere? And maybe just as a secondary point, can you maybe talk about to the extent the agentic solutions gain traction in the market, what is the impact on the company's gross margins?

I'll take maybe the first one, and Shelagh, you can address the second one. Pricing conversation with customers, they don't go far unless you're able to deliver more value to the customer. In EDA, typically, there's a renewal cycle. When the renewal cycle comes in, customers assess their needs. And that's the opportunity to inject new technology. With almost every customer right now, the conversation is I need more licenses because I need -- I'm building my own agents or I need to buy an agent from you or I need the new 3DIC Compiler fused with multiphysics because I need to achieve my next program that I need to plan for. So that's really where the opportunity comes in to lift the value that we are getting from the customer based on the value that we deliver.

IP, I want to say, is a different story. With IP, if we're talking about the Factory 2, really the reason we were able to successfully bring in a number of customers in Factory 2 is the scale, the trust, the quality that we have in our IP. It does not mean it's more essential than EDA for chip design. They're equally essential, but the dependency for them to build a customized chip depends on Synopsys. When I go to the extreme and say there are no other options to deliver for a customized IP at the scale that we can deliver, it opened up the conversation with the customer. We need to capture more value given the impact we're delivering to you. And this is where the royalty is coming in. The point I made as well, royalty will be higher than the license that we capture. And that's the other opportunity to deliver value.

Maybe Shelagh, if you want to take.

So let me take the margin. I think about AI in sort of 2 buckets. Obviously, we're working with our customers, everything that Shankar and Sassine talked about. And our cost doesn't really change. So a lot of that is accretive to margin. Also think about our own internal consumption of AI and the way that we're looking at it is also outcome-based. How do we basically create more capacity for ourselves? We have areas where we are short on engineers. How do we create engineering capacity that allows us to get products out that otherwise we wouldn't? So that's also beneficial in margin because those are products I wouldn't have even had.

I don't want to be accused of prioritizing the front row, so we go to Vivek in the second row.

Vivek Arya from Bank of America Securities. Thank you so much for an informative Analyst Day. I had 2 questions. One, Sassine, for you on the revenue side and then Shelagh for you on the operating margin side. So on the revenue side, Sassine, if we go back to the Analyst Day you had in fiscal '24, at that time, I think you had set expectations of somewhere in the low teens growth. So you're definitely raising that bar towards mid-teens. But the growth rate in the last few years, right, as an industry was lower than that. So I'm just saying as an industry, right, what changes in the next few years to help you accelerate, right, and have more confidence in that growth rate?

And then also a clarification there, how much is the royalties for next year, and as part of your 2030 model? If you could help quantify that, that would be helpful. And then on the operating margin side, you want to grow faster and you want to expand operating margins much faster. Is it that the thing you answered to Jim, which is really just getting leverage? Is there something else? Like what if you were to limit your operating margin, Shelagh, to mid-40s, which is still pretty decent, would you be able to grow even faster, right? Then like what is that trade-off between sales growth and operating margins?

So for EDA, as Shelagh clarified, the 13% is the floor. In order for the company to grow at mid-teens, you need EDA to grow close to where the company needs to grow. Otherwise, just the numbers don't add up. So with that, the confidence we have, given the solution, and I want to anchor on the Multiphysics Fusion monetization starting in '27, will ramp up to the $400 million in '29, AI starting in '27 and the expectation that the rest of the portfolio will grow with the market growth for hardware EDA and as the core -- classic core EDA as you exclude AI and multiphysics.

In terms of royalty, the $1 billion agreement with Amazon, the $1 billion is for license fee, and it's for multiple generations of the 3 products that I mentioned earlier. Royalty is not part of it. Royalty will get captured as they go into production. So the moment they go into production, there's volume and we start capturing royalty. Some of these designs will start in the next few months. So then anticipate 14-ish months of design to tape out and production. And that's when you start the royalty seeing -- start seeing it ramping up. Similarly to other agreements we closed with ASIC with the connectivity as part of that ecosystem, it's roughly in the similar time line.

And I'll make sure I answer. There's specifically no royalty in 2027 for what Sassine just outlined because that ramps over time. The total AOP (sic) [ AOIP ] is $1 billion. That includes licenses and royalties. But obviously, royalties has built up over those generations of chips. We didn't give a split.

Nothing in '27.

Sassine gave the intentionality that we're driving to that royalties will be higher than license. Back to your question on where are we kind of putting the balance between revenue growth and operating margin? Our focus is on both. And what gives us confidence in doing that is everything Sassine just talked about on the business model, and you can think of the royalty as being 100% pure margin over time. So that also creates yet another lever in margin expansion that we didn't have before.

We will not trade off growth opportunities to just raise the operating margin from a 44% to 45% or 46%. We are absolutely investing in the business, absolutely investing while making priority, leveraging technology to do exactly what Shelagh described.

Okay. What we'll do is let's get Jay and then I'll do Josh, and then we'll come back to Jason.

Jay Vleeschhouwer, Griffin. One of your slides earlier showed core EDA as foundational to growth. That's undoubtedly true given the size of, let's call it, Synopsys classic core EDA, which is still your single largest piece of business. However, we talked about this, you and I just a few months ago. That business has shown low to maybe mid-single-digit growth. There's even been some sequential decline in a couple of quarters. So to get from that percentage growth to mid-teens, you would have to add anywhere from $350 million to $400 million a year with that classic business and compound upon that, all else being equal. So what drives that Synopsys classic core EDA business, that improvement over what you've seen in the last year? And then secondly, with regard to the investments you've been highlighting, can you speak a little bit more in detail about what you're doing, particularly on AE expansion and go-to-market?

Sure. I'm assuming when you talk about the EDA classic, you're talking about the core EDA of software and hardware. Just software. Okay. On the software side, there are 2 tailwinds that it's becoming very obvious that we're seeing them, and we are in active conversations with customers as they're looking at the next renewal. So we have a number of renewals that they are -- we're in discussion with customers that they are looking for more capacity for AI. They are looking for the advanced technology that we have, the Multiphysics Fusion.

As we modeled FY '27, and we communicated this a couple of months early, it was modeled based on a bottom-up roll-up of our contribution that comes from multiphysics, AI as well as the growth in the business due to more consumption and more need for that software. As we look for the long term, the double digits is based on further acceleration on all these vectors. So our confidence in delivering to it is fairly high. Otherwise, we will not put it as our long-term guide or for -- specifically for FY '27.

In terms of investments, with AI, the workflow, the engagement with customer is changing, is absolutely changing. As our customers are deploying our full stack or their hybrid approach and further when you go into the OpenAI Synopsys model, the agent is becoming the expert of using -- how to use the tool. And that's very different than the past. Our AE investment needs to evolve and our field investment on how to sell in the world where an agent is becoming the expert user of a task of a domain where you have a model that is able to orchestrate reason across.

And this is not only an opportunity for Synopsys. As you know, the entire software industry is trying to evolve to how does it open up new use cases when you have a model that is able to explore far more than a human can. How do you support the model in that use case? The support is going to come through fidelity checkpoints because whatever the model propose, recommend the tool is generating, you need to have a sign-off to check it. And that's the uniqueness and differentiation we have in our portfolio. This is where the Synopsys Ansys portfolio brings in the richness of that sign-off as we integrate more and these agents are able to generate and validate.

Yes. And I know you know this, Jay, because you are a deep study of it. But when we gave the EDA growth, that does include hardware. And as Sassine gave us a preview for an announce, we will be introducing a new hardware platform. And the need for hardware across our customers is critical because they're building bigger and bigger and bigger, more complex designs, and they absolutely have to have that insight so they have confidence when they go to tape out a product.

Can we make sure that mic is on, please?

Do I need the mic? There we go. Joshua Tilton, Wolfe Research. I thought it was an awesome use of time. And I apologize, maybe I'm going to sneak 2 in here. The first one is just, can you help us understand what the pipeline for these Foundry 2 (sic) [ Factory 2 ] deals look like? Amazon is awesome, but we're always looking for what's next. So help us understand like what some of these deals look like coming down the pipe. And then maybe my second one is, is there anything in the OpenAI partnership that you announced with this GPT-Synopsys that will keep this type of relationship unique to Synopsys? Or do you expect some of your competitors to come out with something similar down the road?

Okay. So I chose my word carefully when I say the $1 billion by 2030 is based on the current agreements that we have signed up. Factory 2 is not limited to a few customers. Factory 2 will expand because that application-optimized IP is needed for any COT. Today, you cannot invest and deliver a competitive COT. And as you know, every hyperscaler is building COT without having an application-optimized IP. The strategy we took, and it's been almost a year in the making is how to use our scale and the current investment in Factory 1, continue on delivering without missing a beat, open up a new factory and have a completely different engagement model with the customer, as I outlined.

We're going to be embedded with the customer from a system requirement to a system validation. The best way to learn how to do it is to run with the leader and the company who has been most successful in building their own silicon. The conversations are happening with others. And today is a very important day that we can right now be more open in the conversations with others to say, and here's the model, here's what we've done, here's how we're doing it. That does not limit our opportunity to IP. While we talk about IP Factory 2, when you're embedded at a system level to a system validation, that brings in the multiphysics, that brings in the packaging, that brings in the whole portfolio. So I cannot be more excited to have a validation point with the lead COT and their ecosystem and start opening it up as we engage further with customers. So that's on IP.

On OpenAI, we don't -- we're not biased. We don't pick we want to work with this versus this versus that. The strategy we took, I want to say close to now 7, 8 months ago, AI labs were approaching Synopsys and saying, I'm experimenting with my model using open source. And I'm saying, I'm seeing something very cool, some good outcome, good results. But I know for a fact, I'll get far better outcome if I collaborate with you. It's a great conversation. But then how do we engage while making sure that we protect the Synopsys IP and the skills and knowledge that we're bringing? The requirement we have is our knowledge and IP cannot get sucked into a model that becomes the base model and without our control is available to the world. That's a nonstarter for Synopsys.

So the GPT-Synopsys was a big investment from OpenAI. OpenAI will have to invest hundreds of millions of dollars to post-train GPT to make a GPT-Synopsys. That does not come for free. So that's a big investment they have to make. The investment we are making is bringing skills, assets, R&D to work with them to fine-tune that model and make it achieve the best outcome between the intelligence and reasoning with our tools. As others are willing and there's a market traction behind that willingness, we'll assess. As far as what do they do with the rest of the market, et cetera, that's not for me to answer. It's really for the others to answer. But we're very pleased actually with the leadership position we took to architect it, define it for the market.

Jason Celino from KeyBanc Capital Markets. Maybe to build off of Josh's question with the OpenAI relationship. Presumably, outcome-based pricing has been difficult to prove in software, right? So can you maybe just tease out what that would look like with this OpenAI partnership because customers, they may be using other models, right? They may be using other competitor tools. So what if there's an outcome where you do improve the PPA, but an alternative method improved it more, would that customer pay in that situation?

Yes. That's why we have 3 choices for the customer. If the customer in lane 2 that they're using our agent, their agent, their model, we're very neutral to that. That's fantastic. We will sell our agents, if they're using any of our agents, if they're deciding to just build everything themselves, they need our tools. And the tools, as Shankar showed in one of his slides, it's anywhere between 5 to 10x for the verification, the VCS Verdi use case that Shankar showed, that they need more capacity. We have customers coming to us, they're needing more capacity for our software because they're using that hybrid lane #2 that I described.

And of course, the same thing applies for the Synopsys stack. By the way, if you're using a full Synopsys stack, the one thing we've been able to demonstrate to customers, you can be more token efficient. Why? We have access to the guts of the tool. We have deep API that they're not available in lane 2 or 3. So again, it's customer choice, 1, 2, 3. The third one, the outcome base. If you heard Greg, the comment he made regarding RSI, where a model can recursively determine the architecture of the silicon in order for the silicon to determine the next architecture of the model. And this is not an OpenAI-only thesis. AI has demonstrated over the last year, 1.5 years, that each generation of models, the capability is truly exponential.

With that frontier reasoning and the frontier intelligence, with our tools being post-trained, our skills being attached to it and the knowledge of the chip design, I have no doubt there will be many use cases that the outcome will be able to achieve much better PPA in a much faster time. In few of the customer engagements that is happening, to be clear, the few customer engagements that they're happening today, they're OpenAI-driven customer engagements, meaning OpenAI buy chips from many. They decide the architecture, they decide what type of spec they need to provide their chip suppliers.

And in the various handoffs, the model is able to prove that use this RTL because it will provide me better power or performance once you take it into implementation. In these early use cases, that's a wonderful opportunity for Synopsys because that's a revenue stream we would not have captured before because we were not there. We did not play. Right now, we're part of that service offering that OpenAI has. Now again, for FY '27, we will see revenue from AI. And as the technology and the partnership evolve, it will only accelerate into the future. There's a question right there.

Yes. We'll go with Lee.

I don't want to get into the middle of who gets the question. I'll be quiet. You decide.

Lee Simpson, Morgan Stanley. Thanks for today, it was very informative actually. Just maybe going back to AOIP. I'm just trying to understand where are you hoping to impact here? Because obviously, interface IP has been something of a go-to for you guys, particularly SerDes and PCIe, et cetera. Is most of this work going to be done around the I/O block? Is that how it's going to work? And where does it stop becoming a chiplet? And then alongside that, it looks to a lot of this is going for the hyperscaler market. Will this include China as well? Will we see regrowth in China?

Yes, excellent question. There are really about 5 IP titles, interfaces that customers are needing desperately an optimization of that IP because it consumes quite a bit of area. The optimization of that IP will provide a higher bandwidth, lower latency. And these are the one that you could imagine what they are, the PCIe, the 224 gig type of an Ethernet SerDes. HBM is all customized. So custom HBM, it's to optimize the logic to memory interface. UCIe, even though it's called a standard, there is nothing close to a standard the way UCIe is implemented by many customers.

Now the way we have engaged with AOIP with the customers, we are not picking and choosing which IP needs more customization, and I'll pay you only for this. They will come to Synopsys for their IP needs for a system. And the reason is a customization fee, not an NRE. It's a -- think of it as a priority fee to put our scarce resources to work on that engagement. And based on that, we will capture the royalty. So will other customers ask for it beside the hyperscalers? Yes. I want to say, over time, meaning if you are looking at an IP optimization for robotics, for automotive, it's really a trade-off. How much do you get by customizing the chip? And do you, the customer wants to make that investment to customize that chip.

Now the decision Synopsys needs to make, is there much upside if we do that effort because, again, it's a royalty base and scarcity of resources to deliver to it. As far as China, the China opportunity as it relates to IP has slowed down, in particular, for the most advanced IP because China is unable to design in China, the most advanced IP. They don't have access to gate-all-around. They don't have access to 3DIC. So it's not us our desire to do it. Our Chinese customers are looking for ways to continue on investing and designing given the restrictions and constraints. We will absolutely engage with them in a similar model as we have for the rest of AOIP, but it all depends on the when, the how to drive it.

Okay. So we'll go to Andrew, then we'll get Charles and then Ashish.

Andrew DeGasperi from BNP Paribas. Just in terms of the 3 lanes you discussed earlier, I was just curious to know -- I'm right here -- just curious to know which one do you think delivers the best economics to Synopsys, if you were to like fast forward in 4 years? And which one do you think would be the most popular with your customers?

I missed the first part. For AI?

Yes, AI monetization.

The 3 revenue stream.

Full stack, customer-owned platform and I think frontier models.

Today, I want to say most of the exploration is in lane #2, naturally because customers, they are all racing to figure out, I'm seeing some good outcome with AI. How do I integrate it into my workflow? How do I change the way I'm doing design, leveraging AI? Almost every customer in lane #2 have came to Synopsys and said, you know what, for the debug agent, for the linting agent, for whatever other agent, you already have it, I benchmark it. I don't need to do it myself. I'll buy it from you. That's why it's not where does Synopsys make the investment? We will absolutely continue on investing on having the full stack because that investment in the full stack are needed for 2 and 3 because the OpenAI, I go back to what is the relationship with OpenAI.

Synopsys is bringing not only the tools to train the model, we are bringing our agents. We're bringing our workflow. So today, most of our customer engagements are in 2, then 1, then 3. Do I envision there will be more post-trained models, frontier models, similarly to what we've done with OpenAI with other companies that they see the same opportunity that OpenAI is seeing and they're willing to invest in it? I believe, yes. It will absolutely expand there because investing in a frontier model and frontier intelligence, you're not going to make money by just having the intelligence. You're going to make money by having the whole stack, including the compute, the service that comes with it for different markets.

And engineering, it's such a sweet market to -- because it's complex, can you bring in that added value? So I do believe it will -- lane 3 will expand beyond one frontier relationship that we have right now with OpenAI. I believe lane #2 will mature and use more of Synopsys agents more because the customer does not need to reinvent and put their resources if the agent is doing a better job that they can get from Synopsys. And that's how the EDA matured over the years, customers or IP, they build their own, then they say it's not worth the investment. I can get good support and a competitive offering from Synopsys. So that's how it is today, and that's how I see it going into the future.

Charles?

This is Charles Shi from Needham. I have a question on lane 3, lane #3. I think one of the things people were worried about throughout this year has been, can AI design chips completely bypassing the EDA tools. And there has been a thought that, okay, to post-train the AI model, you do need the design data and frontier model companies, I mean, maybe except one, don't have chip design data. But when you do this collaboration, there seems to be a possibility for them to use your EDA tools, generate synthetic data to train the model.

So the question is this, does this eventually evolve to a future where there's actually going to be fewer tool costs or maybe no tool costs at all in the future? You completely just use the models. And that's question number one. And the other one kind of related to this, I understand this is a specialized model. The Synopsys IP is contained within that model. It doesn't go to the general purpose LLM. But will your customers be concerned about connecting their data into this model because there's probably going to be multiple customers using the same specialized model and how are they thinking about protecting their own data? So that's the second question. I think this is going to be related to the adoption, any inhibitor to the adoption.

Yes. So on the first question, definitely not. There will not be a point where you can bypass EDA completely. And the model -- how will the model create a placement of the gates that the RTL -- once you create an RTL, you synthesize it, you have to place it, you have to route it, you have to create the clock tree for it. All of that has to obey the rules of manufacturing that comes from TSMC or Intel or Samsung. Do you know how often these rules are updated?

Sometimes customers get new PDKs 2, 3 times in 1 tape-out. Who validates them? The model cannot do that. The model can reason, recommend, explore. Let's assume in some cases, it can generate. When you generate, you need to validate, that you need to validate that step C can go to step D without wasting energy then you get to GDS and TSMC will say, no, thank you. This is violating all kind of my physics rule base. So I don't see how a model can bypass EDA generation -- generating of data and signing off and checking the data.

As far as question number two, that has been a big part of the conversation with OpenAI. As I mentioned, there are already a number of customers in that model where OpenAI, that's not a Synopsys. OpenAI will own the security, the containerization of the customer data, protecting the data, securing for the customer that the data is protected. Same when Synopsys engaged with the customer in the classical model. If we get a customer data or use case or what have you, we lock it up for each customer, so there's no contamination.

In that new model, that is owned by OpenAI. What we do in that relationship, that's why I go back to it's a service relationship that covers many aspects. What we bring in are the tools, the agents, the skills where the model, et cetera, will be run and through the OpenAI either on compute or where they host the model can be through AWS, through Azure, through whomever. That discussion has happened with a few of the early customers, and those are leading customers that they are comfortable with the working model and how to engage that way.

Back of the room.

Ashish Bhandari from Throughline Capital. I just had one follow-up on GPT-Synopsys. I think this opens the aperture to partner with OpenAI on different fronts, including on the traditional Ansys simulation portfolio. I guess I'd be curious what those kinds of partnerships could look like in the future and just how those conversations are going?

Yes, we'll absolutely expand beyond semiconductor because it's the same problem. As I mentioned in one of the S&A slides I had, there is the surrogate model evolving into what Shankar presented, the autopilot to frontier model for physics. So it will absolutely evolve there. In semiconductor, the workflow is fairly well defined. So I want to say the scope of the engagement, the workflow with the customer is fairly well defined. In simulation and analysis, different industry has a different workflow if you're working within automotive, with aerospace, with robotics, with drones, but the opportunity is absolutely there. There will be an expansion. It's not limited for semiconductor, and these discussions are happening. As they evolve, of course, we'll be very excited to share with you how do they evolve and how do we monetize them.

Gary?

Gary Mobley at StoneX. Thanks for hosting this event, very informative. So under the idea that some of these long horizon A agents are market expansion opportunities. I think that's another way of saying you can drive higher average deal sizes at customer renewal. So assuming that somebody takes AgentEngineer in its most fully loaded form, how incremental can it be for a license renewal with a long-time customer? And then maybe if you can help explain how using AgentEngineer or any other customers' AgentEngineer, how that drives more usage of traditional EDA copies per chip design specifically?

Yes. Shankar mentioned we have 50-plus current engagements. Those engagements are mostly around our AgentEngineers sitting at our customer platform. There are a few engagements that we are offering the complete platform. And the platform is much more than just the orchestration of the agents. There's a lot of telemetry and intelligence that goes into connecting from the compute layer, model layer all the way up to the domain-specific agents. The example we showed where it's 5 to 10x more VCS and Verdi licenses for that particular use case.

Our customers are seeing it. We have a number of renewals discussions happening today with customers that they are constrained by licenses. They're saying, I don't know how much I need. I don't want to overcommit. That's why we're offering both a subscription and a consumption for the license, regardless what you're using for the subscription or the platform or the agent. With a few large customers and they happen to have renewal time line in the window that we're talking about, the conversation right now is how do we provide flexibility as our customer is learning because they're not going to commit for 3 years at a certain level of capacity if they still don't know yet what capacity they need. The one thing they know is I need more capacity.

And as you know, each customer engagement is different. It depends on the baseline of the tools they have, how do they grow it, et cetera. That's why the -- I go back to the confidence we have that it is more consumption for the tool because we're having these conversations with the customer. How much of it will be consumption versus the classical subscription? In this early stage, it's primarily the customer comfort zone is subscription because that's what they're used to. They're comfortable with it. We're completely okay with it. That gives us a much better visibility and revenue streamline that is very predictable. So it's a meeting the customer where their needs are at. That's the approach we're taking right now. And in each one of those cases, it's starting at the most fundamental layer, which I need more licenses from you.

All right. Well, is that Kelsey? I can't see.

[ Kelsey ] from Citigroup. So I have a question on operating margins. As you build out your factory to more customers, would you need to allocate more R&D dollars there? And would that impact your long-term operating margin target?

I've answered that before in the following way. We were already doing customization for customers, but we were not getting paid for it. So that's why our confidence, if you remember, 2, 3 quarters ago, we're like we know how to do it. We've been doing it. We charge for it as NRE. So our engineering team, we know how to do it to the earlier question, why do you stop at IP, not a subsystem. We are delivering subsystem to customers. We're delivering, in many cases, customized IP. The Amazon engagement, what is unique to it, and I'm truly looking forward for us to learn how to be embedded early at the system definition all the way to the system validation.

That does require some new skills, and Charlie and team are expanding and prioritizing these skills as we had many, many conversations with Amazon to set the right expectation of what does Synopsys own, what do they own, what's the handoff, how do we become part of their team. All of this took the last 4, 5 months of conversation to say, here's the engineering expectation and the type of engineering I need to move forward.

From an operating margin point of view, and I'll have Shelagh comment more on it, the reason, again, we have the confidence that the operating margin will only improve is, again, we were doing a lot of the work. Right now, we need to get paid for the work at a much higher rate than what we have been getting paid for. And the opportunity to use a new method of customer engagements and technology, we're absolutely absorbing it at a fast pace inside our IP R&D team.

Yes. And Kelsey, the operating margin does include investing in AIOP (sic) [ AOIP ] and building out that factory to support those further customers and designs. So that's fully incorporated. And over the horizon, we add in royalty, which is also 100% margin. And we've not had that before in our business.

All right. Thanks, everyone. I know there's other earnings today, and you guys want to get to those. Sassine, if you just want to close out and say thank you.

No, really, thank you so much. I hope our enthusiasm and excitement around how do we take advantage of the market opportunity and redefine our business model in IP, in EDA and in physical AI. I truly cannot be more excited about our opportunity, and I look forward to every quarter, committing and delivering and we do what we say and say what we do, and we need to keep up with that promise. Thank you for taking the time and look forward for more conversations with you. Thank you.

This concludes Synopsys Investor Day. A replay of today's program and the accompanying materials will be available on the Synopsys Investor Relations website.

Ladies and gentlemen, welcome to the Synopsys Earnings Conference Call for the Third Quarter Fiscal Year -- as a reminder, today's call is being recorded. At this time, I would like to turn the conference over to Tushar Jain, Vice President. Please go ahead.

Good afternoon, everyone. Welcome to Synopsys' Third Quarter Fiscal Year 2026 Earnings Call. With us today are Sassine Ghazi, President and CEO of Synopsys; and Shelagh Glaser, CFO. Before we begin, I'd like to remind everyone that during the course of this conference call, Synopsys will discuss forecasts, targets and other forward-looking statements regarding the company and its financial results. While these statements represent our best current judgment about future results and performance as of today, our actual results are subject to many risks and uncertainties that could cause actual results to differ materially from what we expect.

In addition to any risks that we highlight during this call, important factors that may affect our future results are described in our most recent SEC reports and today's earnings press release. In addition, we will refer to certain non-GAAP financial measures during the discussion. Reconciliations to their most directly comparable GAAP financial measures and supplemental financial information can be found in the earnings press release, financial supplement and 8-K that we released earlier today. All of these items, plus the most recent investor presentation, prepared remarks and Investor Day information can be found on our website at www.synopsys.com. With that, I'll turn the call over to Sassine Ghazi.

Good afternoon. Synopsys delivered an outstanding third quarter with revenue, non-GAAP operating margin and EPS all exceeding the high end of guidance. These results reflect broad-based strength, including outperformance in EDA and ANSYS and continued growth in IP. We are raising our full year revenue, non-GAAP operating margin and EPS guidance. In addition, we expect EDA growth to accelerate in Q4 and to deliver double-digit growth for the full year.

The key takeaway from Q3 is that the fundamentals across our portfolio are strengthening. EDA is accelerating. Design IP has returned to growth and ANSYS is performing strongly while beginning to create new growth opportunities across the combined portfolio. This quarter marked 1 year since the ANSYS acquisition closed. And in Q3, we launched our first joint Synopsys and ANSYS solutions, multiphysics Fusion.

I want to recognize our global team for executing with focus and agility to integrate our world-class capabilities. The combination has strengthened our competitive position, expanded our opportunity and enabled us to deliver differentiated solutions addressing the physics challenges of modern chip design. Industry trends are aligned to our strategy and our strengths as the leading provider of engineering solutions from silicon to systems. Unprecedented design complexity driven by the demands of AI is fueling the need for the IP and design solutions necessary to deliver next-generation AI compute, infrastructure and physical AI systems.

These trends are evident in our Q3 results. Starting with design automation, which achieved healthy growth in Q3, underpinned by strength in EDA, including record hardware revenue. We expect this momentum to continue with EDA growth accelerating to double digits in Q4 and for the full year.

Design activity is highest among AI and high-performance compute customers, developing increasingly specialized chips with multi-die architectures, more complex packaging and system requirements. These are all areas where Synopsys leads. AMD's recently launched Instinct MI455X GPU is a good example. To deliver this highly sophisticated new product series, AMD leveraged Synopsys' 3DIC compiler, the industry's only exploration to sign-off platform for multi-die and advanced package co-design and optimization.

The complex software and system requirements of AI compute also drive demand for our hardware-assisted verification solutions. We secured 12 new and 66 repeat HAV customer wins in the quarter. As I mentioned, the launch of multiphysics Fusion was a major EDA milestone in Q3 and creates a new growth opportunity for Synopsys.

Multiphysics Fusion combines Synopsys and ANSYS technology in the industry's only solution with thermal analysis fully integrated into the chip design flow. Customers, including NVIDIA, Cisco, MediaTek and Samsung Foundry have validated up to 10x faster design closure and 3x faster run time. This drives greater value for our customers and also for our products. We expect these add-on capabilities to begin contributing to EDA growth in 2027. Agentic AI is another growth vector for.

Synopsys, and we demonstrated strong progress in Q3. At the DACH conference, with NVIDIA, we showcased a fully autonomous long-running design verification agent that can orchestrate the entire chip verification cycle and deliver up to 50x faster time to validated RTL while achieving 20% additional coverage improvement. With Microsoft and AMD, we introduced the first autonomous EDA workflows on Microsoft Discovery that can automate debug implementation and design closure.

Early engagements show up to 40% reduction in debug cycle time, saving weeks of engineering effort while improving design quality. We're seeing strong customer interest in our Egentic AI platform with more than 30 active customer engagements underway. Early feedback has made clear that as these agents take on more engineering work, they orchestrate our underlying EDA tools at a significantly higher rate that allows customers to run more design and verification workloads, creating an incremental growth opportunity for Synopsys as we capture our fair share of the value that these Egentic workflows and foundational tools provide for our customers.

Turning to Ansys. One year into our integration, Ansys continues to see strong demand. From semis to aerospace to industrial and more, companies are embracing digital engineering. Across industries, ANSYS simulation is accelerating innovation while reducing development risk and cost. For example, a leading automaker is using ANSYS SIM AI to achieve roughly 98% prediction accuracy and move crash analysis to near real time.

And a leading heavy equipment manufacturer achieved more than 10x faster motor design. We're applying AI to extend our SNA leadership and further automate the simulation of complex systems. This includes expanding our portfolio of GPU-accelerated Ansys applications.

And in Q3, our largest Ansys deal was for GPU-accelerated Ansys CFD to support a company-wide digital twin at a multinational electronics component maker. Turning to design IP, which grew sequentially and year-over-year on broad AI infrastructure demand. As AI drives demand for higher bandwidth, faster connectivity and more complex system architectures, our interface, memory and die-to-die IP portfolio sits at the center of the stack. and our Q3 results showed it.

We won more than 95% of PCIe 7 opportunities, including a subsystem win at a marquee enterprise storage customer. In LPDDR 6, silicon proven across multiple nodes and foundries, we've secured 25 design wins year-to-date. Our die-to-die business is on pace to double year-over-year, and we now have more than 100 cumulative design wins. The industry continues to rely on Synopsys for silicon-proven quality and unrivaled scale.

Our standards-based build once, sell many IP model remains foundational to our growth strategy. We'll continue to invest and grow this business, what I call Factory 1, which benefits from strong chip start activity and solid traction across industries. For example, in automotive, we've sustained a 90% plus design win rate for 3 consecutive quarters as ADAS platforms refresh on to 5 and 3-nanometer. In mobile, consumer and edge AI, our USB IP has now crossed $2 billion in lifetime bookings with Tier 1 design wins already moving to the leading edge node.

As AI expands beyond digital infrastructure into physical products, demand for silicon will continue to expand, providing a tailwind for our standards-based IP business. The higher growth opportunity in IP lies with a growing set of AI customers who are asking for deeper collaboration and IP solutions optimized to their specific workloads and architectures.

To meet that demand, we are expanding into differentiated IP subsystems and enabling custom silicon solutions. Customers ranging from hyperscalers, ASIC vendors, foundries and classic semiconductors want to partner with Synopsys to accelerate their chip development efforts and leverage our IP and engineering expertise to build increasingly differentiated custom silicon. This is our factory I model for customized IP. It moves us up the value chain from licensing alone to licensing plus royalties and positions us to capture the fast-growing custom silicon opportunity.

This is a large focus, and we are making strong progress. We are in active discussions with multiple Fory-I customers, and I look forward to sharing more at Investor Day. To summarize, I want to thank the entire Synopsys team for their continued focus, innovation and execution. Q3 reinforced the strength of our strategy and our confidence in a strong finish to the year.

AI is driving demand for advanced silicon, system-level engineering and AI-powered design. Our leadership portfolio positions us to capture a greater share of R&D investment across industries. We remain focused on translating our technology leadership into sustainable growth and margin expansion. Now over to Sheilagh.

Thank you, Sassine. We delivered an outstanding Q3, achieving revenue of $2.477 billion, non-GAAP operating margin of 41.6% and non-GAAP EPS of $3.91, all beating the high end of our guidance range. With broad-based strength across the business, the revenue outperformance was driven by EDA as well as strength in the ANSYS business.

Backlog remained very strong at $10.9 billion, modestly down quarter-over-quarter due to the divestiture of the processor IP solutions business that closed in Q3. With the strength in Q3, strong cash flow generation and continued momentum into Q4, we are raising our full year revenue, non-GAAP operating margin, EPS and cash flow guidance.

I'll now review our third quarter results. All comparisons are year-over-year unless otherwise stated. We generated total revenue of $2.477 billion, up approximately 42%, including ANSYS revenue of approximately $711 million.

As Sassine noted, 1 year into the combination, ANSYS continues to perform strongly. We are also ahead of the schedule on the cost synergy commitments we made at close and have repaid the term loans earlier than planned. Total GAAP costs and expenses were $2.119 billion with GAAP earnings per share of $2.84. Q3 GAAP EPS includes a gain associated with the sale of the processor IP solutions business that closed in the quarter.

Total non-GAAP costs and expenses were $1.446 billion on the lower end of our guided range as we continue to improve operational efficiency and deliver ANSYS cost synergies ahead of schedule, resulting in non-GAAP operating margin of 41.6%. Non-GAAP earnings per share were $3.91, ahead of our guidance, underscoring our strong operational execution in the quarter. Now on to our segments. Design Automation segment revenue was approximately $2 billion.

As a reminder, this excludes the Optical Solutions Group, which was divested in Q4 '25. Within the Design Automation segment, Q3 EDA revenue increased 8.5% year-over-year, reflecting robust EDA software performance and another record quarter for hardware-assisted verification solutions.

Design Automation adjusted operating margin was 45.2%. The Design IP segment returned to growth with revenue of $474 million, up approximately 11% year-on-year. Consistent with our outlook, this represents continued sequential growth in the IP segment as we repositioned the portfolio to focus on the highest value opportunities.

Design IP adjusted operating margin was 26.5%. Turning to cash. Free cash flow was $746 million in Q3, and we ended the quarter with cash and short-term investments of $3.6 billion. Total debt at the end of Q3 was approximately $10 billion.

Now to guidance for the full year. We are raising our total revenue guidance by $50 million at the midpoint, driven by strength in Design Automation segment led by EDA. As Sassine stated, momentum in EDA remains strong, and we expect double-digit organic EDA revenue growth in Q4 and for the full year 2026. We continue to expect the IP business to grow sequentially in Q4.

This results in a revenue range of $9.69 billion to $9.74 billion. Within that, ANSYS revenue contribution is expected to be approximately $2.98 billion, up $20 million versus our prior guidance. Next, expenses. Total GAAP costs and expenses are expected to be between $8.667 billion and $8.742 billion.

This includes an increase in expected charges for fiscal year 2026 in relation to our previously announced restructuring program as we continue to accelerate our committed synergies.

Total non-GAAP costs and expenses are expected to be between $5.67 billion and $5.70 billion and non-GAAP operating margin of 41.5% at the midpoint, a 50 basis point raise to our previous guidance. GAAP earnings are expected to be between $3.84 to $4.08 per share.

We expect non-GAAP earnings of $15.04 to $15.10 per share, a $0.31 increase at the midpoint from our prior guidance due to higher revenue and increased operational efficiency. We are raising our cash flow from operations guidance by $500 million to approximately $2.8 billion on strong cash collections and reducing our CapEx guidance to approximately $225 million, resulting in free cash flow of approximately $2.6 billion, an increase of $600 million versus our previous guidance.

Now to targets for the fourth quarter. Total revenue between $2.53 billion and $2.58 billion, total GAAP costs and expenses between $2.225 billion and $2.3 billion. total non-GAAP cost and expenses between $1.45 billion and $1.48 billion, GAAP earnings of $0.60 to $0.85 per share and non-GAAP earnings of $4.10 to $4.16 per share. Our press release and financial supplement include additional targets and GAAP to non-GAAP reconciliations.

Thanks to our global Synopsys team for another strong quarter. These results reflect strong execution across the business, continued demand for our technology and disciplined operating performance as we build the foundation for the next phase of growth. We look forward to seeing many of you at our September Investor Day to discuss the compelling long-term opportunity we have as a mission-critical partner for our customers.

With that, I'll turn it over to the operator for questions.

[Operator Instructions] Your first question comes from the line of Jason Celino with KeyBanc Capital Markets.

Really good results here. I think what really stuck out to me was the 8% EDA growth, which was stable with last quarter despite the harder comp. You mentioned it's supposed to accelerate to double digits in Q4 and the full year. I mean, how would you describe what's driving that incremental acceleration? Is it design start activity? Is it Agentic? Is it just better monetization strategies? Just help us understand.

Thanks, Jason, for the question. Yes, we are very excited about the overall performance in EDA and the acceleration to wrap up the year with double-digit growth, exactly what we have committed to in terms of our segment growth. What's driving the increase in confidence in our business in EDA is driven by multiple factors. The complexity of chip design, the move to advanced package 3D-IC, the example I mentioned in my prepared remarks, like an AMD expansion and use of 3DIC compiler, and there are a number of other customers that are designing the advanced package are using our technology AI is definitely a tailwind as customers are rethinking of how to reengineer their chip design engineering, it's requiring different methods for that engineering. So that's driving another tailwind for us. And hardware, we had a record revenue year on hardware. So all in all, that 8-plus percent is organic growth for EDA that we're fairly excited about.

Yes. And I'd just point out, Jason, that the 8.5% Q3 EDA growth that you saw was against a really tough compare. Q3 '25 was 16%. And so as Sassine said, it really just shows the strength of the business to be able to perform against that tough compare and then have the full year continue to have double.

Yes. And then Sassine, you mentioned something you talked about your customers having to reengineer their processes. We're seeing a lot of innovation happening. Everyone always talks about these new AI models. I think yesterday, there was an example, OpenAI talked about the development of their new chip. They talked about using their own AI models to accelerate the design process. Maybe can you speak to when you hear examples like this because a lot of your customers have used their own models in the past. What is involved in the reengineering of a design process? How much is supplemental or incremental or replacement of something that might be existing? I don't know if that makes sense, but...

Yes, of course, of course. Yes. Thank you for the question. For at least 1.5 years now to 2 years, we've been talking about how AI is reshaping how engineering is done. The investment that Synopsys has been making and leading in delivering agent engineers to our customers in rethinking the workflow, including AI models that will absolutely participate and contribute to that reengineering of engineering. In every case, the underlying requirement is more and more and more of our software. because if you're using an AI model or agents that the customer is developing, it doesn't matter. You still need the ground through physics in order to -- for that model to be able to operate with confidence and delivering to the best outcome. So the example that you mentioned actually is a very good example and a great opportunity for Synopsys on the EDA front. Not to mention, it's a huge opportunity on the IP as well because that's rethinking the whole architecture as you customize the silicon.

Your next question comes from the line of Joe Vruwink with Baird.

I wanted to go back a few years, but at your 2024 Investor Day, you shared an outlook back then around how 30% of EDA software demand might end up coming from multi-die efforts by next year. I'm curious how that figure might be tracking and maybe what you see after 2027. I think we all appreciate there's been quite a lot of recent attention even this week on HBM. How might EDA content change for you when thinking about DRAM processes moving to logic, that sort of thing? And is it actually strengthening maybe relative to what you thought a few years ago?

Yes, Joe, actually, that forecast has accelerated. As I mentioned in the prepared remarks as well, the die-to-die wins that we've had in the last 12 months have doubled. And the reason for that is this whole advanced package and 3D-IC architecture. That drives a significant opportunity in IT. Die-to-die is one example then, of course, all the other interfaces that are required to stitch the system together as a final product at our customer.

And on the EDA side is 3DIC compiler, and this is where the emphasis of the joint solution with ANSYS is essential. You cannot build these systems without taking into account physics, thermal, structure, fluid. -- into the chip design phase. So the 30% back then was the figure we thought was a stretch, but it absolutely accelerated given all the investments our customers are making to build these efficient custom silicon.

Okay. That's great. I wanted to ask the double-digit organic growth in EDA. If you think about splitting that up between software and hardware, is the performance in your software business where you would like it to be here at year-end? It seems like hardware has remained a very large and strong driver. I'm more curious about the software performance.

We're very happy with the software component actually. Very, very pleased. The part that actually I'm most excited about is the delivery of our joint solution with ANSYS. And that gives us the platform to deliver to where the future of engineering challenges is heading. As we just talked about, the advanced package, the need for physics into electronics gives us even the confidence to look at the trajectory and continue on delivering these double-digit growth.

Your next question comes from the line of Charles Shi with Needham & Company.

Sheila. I have -- maybe this is for So. I have a high level -- maybe a long-term question. Sassine, we know that going back probably more than 10 years, you played a very pivotal role in terms of infusing AI. I know back then, it was not a large language model, probably more like reinforcement learning type of AI into the Synopsys tool flows, DSO.ai, all those great products.

But AI has advanced so much over the last 10 years, especially last 3. So the question I constantly hear from investors is about that, is there any risk for AI to actually disrupt the commercial EDA business? And I think one -- at least one school of thought was thinking, could there be an end-to-end what they call AI native chip design that bypasses all the commercial EDA tools, especially maybe with some AI models trained by the commercial EDA generated synthetic data. Is that a real threat in your opinion to the overall EDA industry at all? Or where do you see where AI can be more substitutive or complementary to the commercial EDA business?

Yes. Thank you, Charles. I don't need to go back or go as far as 10 years ago. You're right, around 2017, we introduced and invested and saw great results with DxO.ai centered around reinforcement learning. If you look at the last 3 years, the focus was around Copilot, generative AI, move to agents. Right now, we're talking about autonomous designs. As you start looking at autonomous workflow, the most important thing is accuracy and determinism. Customers will not invest hundreds of millions of dollars in a product without having the confidence that it's going to work.

The portfolio we have with the sign-off leadership is essential to building these autonomous workflows. We are participating with our customers on how to achieve an autonomous workflow. It's not like it's happening without our participation. We're proactively engaged with them to reengineer how they're looking at the future of engineering with AI being the center of that evolution.

I am not worried at all that at some point that, that model can do the end-to-end without our participation because you have to remember, these models are not static. They're constantly changing. They constantly need to learn -- so the opportunity is the opposite. It's not a threat, it's a significant demand for our software to train, to inference, to constantly enable that faster design to deal with the complexity and we're at the center of it.

Maybe Sassine, on the genic AI agent opportunities, how should I think about any uplift to the overall revenue growth, especially EDA growth and -- and can you give us an update on the changing the business model more to the subscription plus consumption, at least for the agents any discussion with your customers so far?

Yes, number of engagements. Actually, the first question you had, as our customers are exploring whether to use an agent some synopsis for an agent plus from Synopsys plus their own agents to keep their special sauce inside their workflow, the customer workflow or the customer agent the need is for more licenses. We are defining with our customers multiple ways on how to engage from a subscription of our agents, subscription of our workflow as well as a consumption measure as these agents and the new workflow is consuming more software.

We'll highlight more of how we're thinking how to model the long-term growth with this context that I just described in a few weeks, September 30. But absolutely, we're in advanced discussions with a number of customers with different flavors of using their agents, our agents a hybrid of both and multiple model optionality that they're thinking about.

Your next question comes from the line of Lee Simpson with Morgan Stanley.

Great. Maybe just a couple of quick ones on IP actually. Maybe just preempting the Analyst Day. I want us to see and if you can maybe just give us a little bit of outline on the speed of shift to the Factory II opportunity you outlined with licensing and royalties. And then secondly, it's been about a year, I think, since we've seen the intrinsic ID acquisition. And I think at the time, you talked about security IP as being a new vector of growth in IP -- just wanted to hear if you could maybe outline the size of that opportunity, how you've seen engagements go. And we had, in particular, you think deployments will happen.

Lee. On Factory II, actually, all you need to look at is the momentum in every hyperscaler investing and are at various stages of delivering their own custom silicon. These chips will not happen without our interface IP. These customers need our interface IP in order to build their own chips and to connect to the ecosystem be it the memory provider or if they're using -- if they are investing in their XPU, but they need a networking chip from their supplier, connecting them together come through our interface IP.

So that's the opportunity. What we could see as well and the reason we started talking about Factory II is the need to customize these standards and to accelerate the delivery of these customizations. Synopsys is in a unique position given our scale and the knowledge that skills the market position to deliver on that customization and acceleration. We are in advanced discussions with a number of these customers to change the business model from the traditional IP license plus some NRE to a license plus a royalty.

I look forward in a few weeks to, again, help you model what does that look like. But I cannot be more excited about the investment that we've made and the agility in pivoting in that direction while absolutely continue on leading and investing in factory 1 because that's another significant opportunity that will continue. As for security, the -- the reason we started looking at the portfolio and we divested the processor IP is to focus on the areas of growth.

Security is one of them. As you said, we don't split it out as a separate item, but we have a great market position in security, and we'll only continue on becoming more and more important, given you need to secure the chip not only at the software level as much as you can do at the hardware level, and that's where our security portfolio comes in. .

Your next question comes from the line of Josh Tilton with Wolfe Research.

This is Arsene on for Josh. Just Sasine,first, you talked about seeing strong early customer interest in multiphasic fusion following the launch. And historically, chip design and simulation often will kind of handled by different engineering teams and different workflows and tools. I guess when you're bringing thermal analysis directly into the design flow, how are customers structurally, I guess, approaching that convergence -- are you seeing those teams start to work more closely together and consolidate around more common workflows?

Or does adoption still kind of require navigating distinct engineering teams in the separate budgets?

Yes, you're absolutely right. These teams or the skills and expertise of engineering or separate domains, they had a different handshake as the design steps are moving from the synthesis to the physical design to sign off, et cetera. The requirements to have codesign is essential to reduce margin and deliver to these competitive products. So absolutely leading customers are requiring to take thermal into account during the design implementation to take structure stress as they're building these 3D IC into the architecture of the chip not only the synthesis or the implementation of the multiple chiplets.

So yes, absolutely. And this is where we have invested that the implementation engineer that's sitting in the upfront part of the design flow are able without too much effort to be able to bring in sign-off accuracy early in the design flow. And that's exactly where we see the opportunity of the combined portfolio and delivering to the fusion of physics with electronics.

From a budget point of view, by the way, the second part of your -- I'm sorry, from the second part of your question, from a budget point of view, as we have committed 1 plus 1 will be greater than 2. What it means even if it's coming from an EDA budget, the joint solution will capture an upside in revenue to the existing separate point tools.

Got it. That's helpful. And then just, Shelagh, just clarifying just one topic specifically on ANSYS to raise $20 million to the $2.98 billion. Last quarter, you helped us with $4.5 million contribution from that accounting dynamic and it was $60 million for the full year. Is it still $60 million for the full year and that raise on that $20 million increase in ANSYS is just core upside from good execution there?

Yes. So last quarter, we talked about the accounting change, and so we made that accounting change, and we'll be making that accounting change and in the guidance that we're giving incorporates that. So we're seeing strength in the ANSYS business, including the channel.

Got it. And what was it, I guess, in Q3, for ANSYS accounting change and it's still $60 million for the full year? Is it a different number this time? .

It's still in that same range for the full year.

Got it. And the quarter was 12.5% or...

We didn't disclose the in quarter. .

Your next question comes from the line of Joe Quatrochi with Wells Fargo.

You talked about a tale of 2 markets with AI versus non-AI and EDA. I'm just wondering if the acceleration that you're seeing is AI becoming a larger piece or in offsetting kind of the non-AI -- or have you started to see also some acceleration from the non-AI part of your business as well?

Yes, Joe, the -- so the reason for our assertion to begin with, what we do on a quarterly basis, that these are internal measures that we have is we track chip starts. And the reason we have a good coverage on design starts is our IP portfolio. There is no customer that is planning a new chip start that we don't engage very early on through our IP portfolio. And of course, EDA will follow. The observation is on the non-AI, in the last 2 quarters, it has stabilized. What it means was we were observing a slowdown in design start in the non-AI segment.

In the last couple of quarters, stabilization. So it's not declining anymore. Now on the flip side for AI, where we have been seeing and continue on seeing an acceleration in design start, which is a great balance for the opportunity that we have.

That's helpful. And then maybe as a follow-up, just wondering if you could give any puts and takes on the RPO, down such this quarter. Was there any impact from the divestiture? And did it come in as expected with your plan?

Yes, it came in as expected. And as I said in my prepared remarks, the modest change is really due to the divestiture of the processor IP business that happened inside the quarter. As you recall, we were close to closing the deal when we did last earnings it closed a few days after we did the earnings. So that's why you're seeing it this quarter.

Your next question comes from the line of Siti Panigrahi with Mizuo.

Sassine it's a really a good quarter. Congratulations. Going back to the ANSYS and Synopsys, the integrated products that you launched, I think you talked about that multipageusion is not expected to contribute to EDA growth until 2027. So can you talk about the adoption of pipeline trajectory that we should expect from now and then -- and is that '27 contribution more likely to show up as an incremental EDA growth? Or as share gains from your anti simulation base? Any color like what you are seeing in terms of pricing benefit, value to the customer on that, that will be great.

Yes. So from a value to the customer, the 10x faster design closure or a 3x faster spice accurate multiphysics timing, that is a significant value to customers. What does it mean for the customer, less iteration, better design, faster. So -- our customers in these early engagements have validated and they're in early stages of deployment. The moment we move to production, which those customers will move to production, we'll start seeing the revenue upside.

As we've said from the beginning, FY '26, we will not have much contribution in the joint solution. It was a year of execution, delivering to these products -- as we look at FY '27, absolutely, it will contribute to our growth in EDA. We are absolutely committed as well to the $400 million synergy in year 4. So as we meet in September, we'll be able to start talking about '27 and the longer-term contribution of this differentiated solution.

That's helpful. And then a quick follow-up. I know Mike Elo has been there now a few quarters. How is it driving the sales organization any kind of specific changes he is contemplating or has been working towards as you roll out this indicated product?

Yes. Mike has been doing a great job in leveraging what the organization does incredibly well and the areas that we need to increase our investment from portfolio, go-to-market point of view, et cetera, et cetera, the priority as we look at FY '27 and beyond is how to engage the customers in the areas of differentiation and ensure we have the right investment with the customer we're enabling the customers successfully so we capture the monetization opportunity.

So Mike has been spending a lot of energy internally with the team to prepare the organization for IP Factory II for the AI monetization, for the joint solutions. All this is a significant time where Mike is spending as we look at '27 and beyond.

Thank you. He's a great hire. Thank you.

He is. We're happy having him. .

Your next question comes from the line of Jay Vleeschhouwer with Griffin Securities.

Sassine, for you first. This may be an imperfect analogy, but how would you compare the prospective migration or adoption benefit of the new multiphysics cohort and cohorts to follow might compare with the ICC diffusion compiler transition, that obviously didn't include ANSYS component at the time, but that was your last big architectural or generational change in our stack. So how would you think this one now is underway might compare to that? And then a follow-up.

Yes. Jay, thank you. Actually, a very good question. What we've done with Fusion was bringing our sign-off capability and strength into the design physical implementation phase because the customers at the time were having to iterate late stage to correlate or to sign off the chip. It's exactly the same here, but you're including physics. Now the Red Hawk, the HFSS, the rest of the portfolio of ANSYS how do you bring not only proximation into the design phase, how do you bring the actual engines into the design phase so you reduce iteration, you have a convergent flow, et cetera.

The investment we made in the Fusion platform, because remember, the Fusion platform is not about bringing tools together with a common interface or a user interface. We made a significant investment at the data model level. So we -- so our R&D team can write code optimize on the same exact infrastructure and data model. And that's where Shankar and team have been investing quite heavily from day 1 of the integration start to deliver to exactly the same value that we were able to build on with Fusion. .

Okay. Secondly, the reengineering of engineering concept that you've talked about now since CONVERGE last year remains a very interesting concept and prospect for you and your customers. The question is, what are the ingredients that customers need to make that work? Is it a set of variables or changes they need to make -- is there a single magic bullet that they can implement to make that happen. The demos that you did jointly, for example, at back with AMD and Microsoft around discovery seems quite interesting as perhaps catalyst for some of those changes. So maybe talk about what actually has to happen for the whole reengineering thing to really happen.

Yes. We talked about Fusion as an essential part to have the entire complete set from a spec all the way to sign off. So that's an essential component that Synopsys has that complete set of assets. Now from bringing together a workflow that can leverages the AI speed from a copilot generative AI all the way to autonomy is where we're putting significant investment and racing. The 2 demos we've done, and thank you for mentioning the Microsoft AMD, which was a demonstration of a full autonomous EDA workflow on the Microsoft discovery.

Think how powerful that is, where you can start from a spec and you have a cognitive layer that can orchestrate multiple ask agents in order to deliver to the outcome of the spec. At the same time, what we've done at DAC actually is a demonstration with NVIDIA on an autonomous long-running agent capability. So that's part of -- essential part of reengineering the workflow. What I'm most excited about as you double-click into what I just described is not only the assets that we have, the consumption of these assets is exponential in order to allow for an autonomous flow to deliver to the promise that the customer is looking for, which is an efficient design, better power, better performance, better cost, and that's exactly what we're doing.

Your next question comes from the line of Gary Mobley with StoneX.

Sassine, you mentioned in your prepared remarks, the largest deal in the quarter for ANSYS was a GPU-based digital twin -- was that a large deal because it is accelerated compute runs and accelerated compute versus CPU-based compute. I'm asking because I'm just trying to get a sense of whether the efficiency from an accelerated compute digital twin system accrues to NVIDIA or a cruise to you as well.

Thank you, Gary, for the question. So simulation is a perfect application for GPU acceleration because these are jobs you can, for the most part, not only paralyze you can achieve a significant speed up. So the speed up does not stop or has limitation at 10 or 15x in CFD, we're seeing 40x, 50x, 60x speed up. The bottleneck for our customers is the time to results, the time to accurate results.

And the investment actually started with the GPU acceleration even before the acquisition of ANSYS by Synopsys -- after the acquisition, we just accelerated even further the commitment, the investment and of course, the NVIDIA investment and alignment towards this opportunity only helped -- in terms of who gets the value, we sell and we capture the entire value and uplift the GPU, NVIDIA, of course, in the back end, you need GPU to run from the traditional CPU to a GPU, they benefit that way.

So the large deal is large because of the benefit to the customer and the speed up we were able to deliver to the customer.

And my follow-up, I wanted to ask about Korea. Revenue generated from Korea appears to be trending up close to 20% this year. That's a standout for sure. Is that a reflection of the strength of the memory market? Is it a reflection of maybe, I guess, you retaining more market share at Samsung and what many have speculated? Maybe you can just give some color there.

I'm not sure about the speculation. One thing I can tell you is our relationship with Samsung, with SK Hynix with the broad market in Korea has been a great collaboration in an area in a region that are leading with a very essential part of the AI infrastructure and we are leading with those customers and not limited to those 2 in the broader region itself in across the portfolio. So you need to think of it from IP with our custom HBM and HBM engagements with the lead customers to EDA and to ANSYS. So very pleased with the performance that we have.

Your next question comes from the line of Kelsey Chia with Citi.

Great to see the IT business getting back on track. I believe the team outlined a long-term growth about midteens for IP business several years ago. I mean since then, we have seen significant acceleration in the chip design activity particularly among hyperscalers. And it seems that the non-AI portion of the business is also stabilizing. Given that backdrop, is it unreasonable to think that IP business could keep a much stronger growth than the mid-teens laid out over the next couple of quarters? And if so, are there any factors that could prevent that growth algorithm from being reset higher?

Kelsey, thank you for the question. Your assumptions are good ones, which is more chip start a huge opportunity with custom chips, which I refer to as Factory II, as Factory I continue on delivering and expanding -- and for now, the mid-teens is our long-term guide. We look forward for September where we can share more and provide any updates as necessary.

Thank you. We have reached the end of the Q&A session. I will now turn the call back to Sassine Ghazi for closing remarks.

Thank you for all the questions. One year after the transformational acquisition of ANSYS, we're executing with focus, gaining momentum and extending our leadership from silicon to systems. I look forward to seeing many of you at Investor Day in September. Thank you very much.

This concludes today's call. Thank you for attending. You may now disconnect.

Great. Hi, everyone. Welcome you to Mizuho Technology Conference 2026. And we have a great pleasure to host Sassine Ghazi, CEO of Synopsys. And before I start, I was asked to read this.

Today's discussion may contain forward-looking statements related to our current outlook, expectations and beliefs, which are subject to certain risks and uncertainties that could cause actual results to differ. Please refer to Synopsys' most recent SEC filings for a discussion of risk factors that may materially affect those statements. Did I do a good job?

You did good.

All right. So before even I start, I just want to say that there's so much excitement in semiconductor right now. Just to give a quick intro, EDA company, Synopsys, Cadence, they are kind of the backbone. They are the -- like Jensen says, the indispensable companies or tools for building chip design. So it's a great pleasure to host Synopsys today at our conference.

Thank you.

Sassine, I just want to kick off with this. You recently reported Q2 results, your fiscal Q2 results. Maybe it's great to refresh investors like what's the latest with Synopsys and what's your puts and takes there and how do you want investors to orient based on the results?

Yes. We just reported Q2. We had a fantastic quarter where we did beat on our guidance on revenue, EPS and OM. And actually, we -- given the confidence with Q2, we raised the year on all metrics of revenue, OM, EPS and free cash flow. It's our third quarter that we reported post the Ansys acquisition, which is a significant acquisition for Synopsys, and it's expanding our opportunity dramatically.

Yes. Ansys had a great quarter indeed. But let's get into each of this business. When you step through your business segments, let's talk about some of the key investors focus. Like one of the key metrics is core EDA growth. And last first few quarters, it seems to be softening below 10%, like getting to single digits. So what's the things that investors should keep in mind about the growth? And the point I want to make that how do you get back to the durable double-digit growth that investors are looking for in EDA?

Yes. So the Synopsys portfolio, if you look at it, we have really 3 main categories of the portfolio. You have EDA, IP, and the Ansys portfolio, we call it Simulation and Analysis. We are the leader in EDA. We are the leader in interface IP, and we are the leader in Simulation and Analysis.

In core EDA, in particular, it's very difficult to compare a quarter versus a quarter. The way we look at it is a trailing 12 months. And the reason for that, you remove a lot of noise because inside EDA, there's a hardware business. And the hardware business is very lumpy because of the nature of the revenue accounting, you take revenue upfront versus EDA is a very ratable business. So the first half of '26, we did deliver double digits.

It depends on the comps that you have. And since the acquisition of Ansys, there's a lot of -- I find myself, I'm doing a lot of explanations, which I don't like to spend the energy on explanations, especially when it relates to accounting, we had to divest a number of technology. We kept the Ansys part of the portfolio as a separate from EDA because part of the Ansys portfolio has EDA in it.

So therefore, when you're comparing to the market, you're not comparing apples-to-apples. Our commitment is double-digit growth for EDA with the opportunity to expand beyond with the AI monetization potential that is changing the workflow in EDA. But at this stage and at this point, our long term for EDA being double digits, we remain committed to that.

Is there any kind of growth driver that you can cite like to give that confidence, double-digit growth, specifically like design start activities?

Actually, in EDA, what drove our growth has been complexity. If you go back a decade ago, EDA was growing -- core EDA was growing around the upper single digit. Then it expanded into double digits, and we've had years where it was well into the double digits, driven by many factors.

The design starts, the complexity of design. Our customers cannot design these advanced chips without the participation of EDA. Now there are -- these chips are turning into systems. They are not monolithic chips. They're 3D-IC that require bringing physics into the electronic design, and that was one of the key thesis behind the acquisition of Ansys. How do you accelerate the workload as you're running massive simulation, et cetera?

So there are many layers of monetization opportunities. The part that I'm very excited about is the impact of AI on the workflow of building a semiconductor chip. That's a significant change that is happening as we speak, given the rapid exponential in innovation in foundation models.

Yes. Certainly, we'll cover AI later on, but I want to cover our next other segment, which is interesting is IP business. That has its own set of challenges over the first few quarters, as you know that. But how can investors now feel more confident that worst is behind us and it's a normal trends going forward?

So what we said is Q1 was the bottom. And what you need to expect for the rest of the year is sequential growth from the Q1 bottom...

Which you delivered.

Which we delivered in Q2, and we're committed to deliver for the rest of the year. The part I'm most excited about in the IP business is driven by the market dynamics. What Synopsys has done, we built that business organically. And think of it as a factory. We build an IP based on a standard. We build it once. We sell it many times, and it's a great business model.

In the last 3, 4 years, the big change that's happening at our customer base, especially hyperscalers, they're looking for different compute alternatives in order to optimize their TCO. So there's a big trend not only to buy merchant chips or ASIC, is building their own chips, COT. This COT cannot happen without Synopsys IP. And I know this is a big statement. COT cannot happen without Synopsys IP.

Therefore, there's an opportunity for us to monetize COT at a completely different rate than we've had in the past, which is build it once, sell it many times. Why? In COT, in order to make that chip competitive, you need to customize the IP. So it's no longer -- even though it's a standard, you need to customize the standard and deliver it before the standard is finalized. We know how to do it. We have the scale to do it.

We have the skills to deliver to it. We are in active discussions with many of these hyperscalers to change the business model from a use fee only to a use fee and a royalty so we can participate in the upside. I cannot be more enthusiastic and excited about that part of the business that we have.

No, that's a great point. Like you said, COT cannot happen without Synopsys IP. But how should we think about this royalty model that you talked about, which is kind of incremental revenue to what you get right now. But when should we start thinking of that flowing into your P&L?

Yes. So given the number of changes happening in our portfolio, and it's really the year 1 of the Synopsys Ansys integration, we have an Investor Day coming up September 30, where we map out exactly the question that you mentioned. But if -- at the highest level, think of the Synopsys IP of Synopsys -- the Synopsys IP will have 2 business models.

Think of it as factory 1 and factory 2. Factory 1, build it once, sell it many times. That's a fantastic business. We do very well in that business. That will continue. We're building factory 2 for the customized IP. Any IP that's customized, which is pretty much every AI hyperscaler, COT requires that customization, we'll move to factory 2, which is a new business model.

There, the license fee, that's what how we've been monetizing. The royalty upside should be fairly meaningful in upside in order to justify even us talking about it or building that factory. So we'll share more what will that look like, not only for '27, but for the next few years in terms of the revenue growth participation.

Yes. I want to touch on other drivers as well because one thing you mentioned that not only IP will bounce back this year, but next year, it will get back to the corporate growth rate. What are the -- royalty definitely one of the thing. What are the other drivers you should pay attention to?

The demand for IP is there. Actually, the fundamental demand for IP is chip start. And in semiconductor right now, there is no shortage in excitement or the need to deliver customized silicon for different applications. And that's for the applications of today. As you look toward the future, more physical AI coming requires more customization of chips, meaning more chip start. That IP opportunity is significant.

We are the leader by a number of factors compared to the #2 in that space. And that gives us the opportunity to scale with that leadership position. So that factory 1, we've always communicated it will be in the mid-teens, and I have full confidence that will be in the mid-teens. Then you layer the factory 2 growth, which should be higher than factory 1 and achieve the growth at that level.

Okay. Great. I think we'll now switch to the next level, next topic for investors that Intel. Intel commentary. I know you guys -- it's a big vendor for Intel or Intel is a big customer. Maybe talk about the background of your Intel relationship. I know it's -- you are the man behind it. And how it has evolved these years, and any meaningful changes in the Intel strategy or relationship post new leadership or even the restructuring, Intel has gone through a lot of changes last year and also a lot of excitement coming on the Intel side as well. So walk us through on that opportunity.

Intel has a special spot in my heart for me because I started my career at Intel. And when I came to Synopsys within like 4, 5 years of my early days at Synopsys, I was assigned to Intel to be the sponsor of the relationship for Intel. And I remember around 2005 or 2006, we introduced the concept to the industry of a primary partner.

Intel and Synopsys. And I remember at the time, it was the first press release in the industry that Intel chose Synopsys as its primary partner. And what that meant is consolidate from Intel internal tools because Intel had a lot of internal CAD tools to Synopsys and over time, continue on consolidating from other suppliers to Synopsys.

That relationship has been an outstanding relationship. Over the years, as you can imagine, Intel had many management changes, many stress points. We went through many renewals and almost every renewal, the discussion on the spend level, the market change dynamics, et cetera, et cetera, was always in the background. Now, I know with Lip-Bu as the CEO of Intel and brought in some management from Cadence, the constant discussion is there going to be a bias you're going to be out of Intel.

And that's not how the industry works. Customers don't choose us because there's a relationship. Relationships and trust are important. They use us because of the technology we provide. You cannot design those chips without Synopsys. Our Cadence has great technology, but so does Synopsys. And there is no advanced chip that will be done without Synopsys. So when you now get back to the Intel dynamics because I hear that question all the time.

The relationship with Lip-Bu, the relationship with Srini, the relationship with the entire Intel management is very strong. There is no direction of nudging or pushing Synopsys out. And when I get that question, I'm in the details. I look at market share and market share drives revenue share. And there is 0 change. Now the negotiation will happen whenever the time is up for the renewal to happen.

And based on the Intel dynamics, the negotiation will take whatever shape, which is no different than any other customer negotiation. There's the other part of Intel, which is Intel Foundry. And there, I can even be stronger in my message. You cannot be in the foundry business. You cannot be in the foundry business without Synopsys.

You cannot on-ramp a customer to come to your foundry without Synopsys IP and foundation IP. We're the bridge. We're the on-ramp from customer to foundry. We have had -- and publicly, we announced a number of years ago, maybe 3, 4 years ago, the relationship with Intel Foundry on 18A. We built our IP on the technology. We have an ongoing engagement with Intel Foundry on IP. I hope that clarifies.

No, that's super helpful.

The doubt that is always in the background when Intel comes up.

I remember your comment saying "I'm not losing my sleep on Intel." So...

I'm not -- because when I lose sleep is when we're not able to deliver to the customer, which is very rare. In the Intel case, not only we're delivering, we have a great partnership and engagement.

Yes. Now let's switching to the AI and the topic du jour. I know it took some time. But moving to this bright AI future ahead of the industry, we are moving through 3 phases of AI compute. One is the training at scale, training and inference at scale and then now physical AI, all 3. So how does the progression translate into a design start and even EDA tool consumption and how Synopsys benefits in that whole AI transition?

Yes. Maybe a quick comment on overall design start in semiconductor because we track design starts very, very carefully, and we have the visibility pretty much on every chip that starts. In semiconductor, pretty much any company that is serving the AI infrastructure, we're seeing continued increase in chip start. What it means, if you're company A, and you have 4 chips per year on your road map, you're seeing it going from 4 to possibly 5, possibly 6, which is great.

You have the rest of the semiconductor industry that's not participating in AI infrastructure, we've seen a decline in chip start. The last 2 quarters, based on our data, it seems like it hit the bottom. We have not seen yet the turn and the increase. Net-net, in semiconductor, so when you combine the both, the aggregate, is it chip start increase, but not at the same rate as the AI infrastructure, semiconductor for AI infrastructure.

For us, chip start is very good because you sell a lot of IP, EDA and hardware to design these chips. Now when it comes to AI and lowering the bar for our customers to design these chips, -- because you have to remember in our industry, one of the bottlenecks have been access to talent. The shortage of talent is real. When you look at hyperscalers with massive money, they're trying to build their semiconductor team. It takes them multiple years to do it just because of the skills required to build that team.

AI is starting to change the workflow of how to build a chip, which is a huge opportunity for our customers to be able to build more chips, you can argue with the same number of people, reduce the time to deliver a chip and the cost to deliver a chip. That will happen only with us evolving the workflow and the way our customers using our products.

So we have many initiatives there in terms of -- not only initiatives, actually, roadmap items, delivery to the customer to bring in pretty much the agentic stack and the orchestration of these agents for our customer.

Yes. The agentic AI engineers, AgentEngineers opportunity.

Yes. Because there is definitely going to be a mix of human engineers running our product to design the chip and agent engineers running our product to design the chip. So from a business model point of view, for at least 2 decades right now, the industry moved to subscription license for a human use. Now there will be another layer, which is consumption of agent use of the software.

That's going to be an incremental opportunity to monetize the agent use of the software. There's a third layer that is starting to show up where there are some AI labs are very interested in fine-tuning their foundation model for semiconductor applications because they believe there's a market opportunity for them.

And there, the discussions with these labs is percent of token revenue upside because the good news, if you look at it this way, our tools are going to be used under the hood regardless what model you're using because you need that solver physics-based solver in order to train the model and inference the model.

Yes. I'm glad you brought it up. Just bring a promotion here, that yesterday, we published a deep-dive note on this thematic report, how agentic AI engineers expanding the EDA TAM from going from tools to the labor.

Yes. Exactly.

This is a big opportunity. Anybody wants to go dig deep into that. We have all the numbers that Sassine is not sharing here. Now switching to the next thing is Ansys. Ansys, one of the key event happened last year, and making the progress on that. So the question always is we get, is 1 plus 1 better than -- more than 2, like that's kind of the question.

So help us understand what's the early fit customer feedback? I know you launched some of the products, the combined product earlier this year at Converge. So what kind of feedback you are getting? And what's the opportunity there?

Yes. We had -- our thesis on the acquisition of Ansys was anchored on the semiconductor chips, especially for AI applications are moving from a monolithic chip to 3D-IC. The moment you start stacking chips on top of each other, you're dealing with mechanical challenges, not only electronics. So the first priority of the Ansys Synopsys integration is delivering a joint solution where we take the Ansys multiphysics simulation leadership position into the electronics digital design flow of Synopsys.

And by fusing that technology early in the electronics chip design, if you're a customer heading in that direction, you'll have a convergent flow, meaning when you're designing that sophisticated chip, you can predict what thermal issues you're going to have, what structural issues you're going to have. We released the first wave of products in March at the Synopsys Converge.

We are actively engaged with a number of customers in evaluating the technology. I know for a fact, there will be a number of customers that will move from an eval into a production use of the technology. And once the customer commit to production use, it means 1 plus 1 is greater than 2 from a revenue point of view.

Most of these customers are already a Synopsys customer and they're already an Ansys customer. The new solution is a new product, new SKU that is priced differently regardless if you have 1 plus 1. Therefore, it will be greater than 2.

So it's not the first time you're bringing this. You did that Fusion Compiler before. How does it compare in terms of traction wise? And what sort of pricing uplift you saw when you did that Fusion Compiler, like similar kind of model.

Actually, with Fusion Compiler, thank you for bringing this up. It brought in timing sign-off, power sign-off into the Fusion platform. The value we saw besides the uplift on pricing was market share gain. We gained share because the customer could see better value than using a discrete product.

They use the fused product. In this case, we're bringing multi-physics fused into the digital platform. So we will win in 2 ways: one, 1 plus 1 greater than 2 opportunity, the uplift. And there will be a market share gain given the solution will be of higher value to our customers.

Okay. I have one more question. We'll open it up for Q&A from audience after this. The path, I think the margin is the next kind of focus. How does the path from current, like, 41% to your mid-40% operating margin plan look like? And what are the specific levers that get you there in terms of priorities and ranking? You talked about synergy scaling AI and all that. How does that give you that path to mid-40%...

On operating margin, actually.

I know I asked the question, Shelagh's question, but...

No, no, that's great. Shelagh and I were a partner on that mission. On the operating margin, we -- this year, we're going to deliver more than 300 basis point increase in our operating margin. And it came through a number of areas of focus. One, portfolio. There are areas in the portfolio we decided to exit. We announced around September time frame a 10% reduction in our workforce and accelerating the integration synergy of $400 million from year 3 to sooner to earlier.

And of course, the best way to continue on improving that ops margin is by focusing on the revenue growth opportunity and delivering on the innovation opportunity. So -- the other point that often comes up in these discussions is your operating margin has been below the -- your closest peer. And it's true, but we have to remember, it took us 20-plus months to close the Ansys acquisition.

During that period, we had very little flexibility to make changes in the portfolio or in the workforce. So we are absolutely committed to get to the mid-40s and continue on expanding the margin as we drive the top line.

Okay. Let's see if there is any question.

As you see your clients adopt [ agentic AI ], what are the key challenges that they are talking to you about in the new paradigm here, an agent could design the entire chipset, entire system?

There is part of the chip flow today that looks very similar to software before you move into the physical implementation of the chip. That first stage, which is called the front end of the design where you provide a spec, then you do a number of steps to create an RTL, which is the language before you move into the physical implementation.

We announced a product in March that is multi-agent adaptive orchestration, where there's a cognitive layer calling multiple specialized agents to go from a spec to a verified RTL. That part of the design looks very similar to the software. So we're seeing nice progress there. The moment you go into implementing the chip physically, that means which foundry are you using, which library from the foundry and PDK, et cetera.

That's where the physics solvers become essential to make sure whatever you're speccing will be able to manufacture. Almost every one of our customers is looking at the hybrid workforce of a human engineer with an AgentEngineer and how to balance not only the work, the cost because an AgentEngineer is not for free. There is a cost associated with the tokens that they use, the compute they use, the licenses they use and the human engineer in the mix.

Now in the Synopsys case, as you get to the final stage, we have the leadership of sign-off, be it from the Ansys portfolio or the classic Synopsys portfolio that is essential before you commit to the chip to go to manufacturing regardless if it's designed by a human or agents or the combination of the 2.

Sassine, a big announcement we heard recently was NVIDIA partnership. And if we look at Jensen Huang's words, physical AI could be a $40 trillion, $50 trillion opportunity. Synopsys is a participant in that through Ansys. You have a partnership with NVIDIA to accelerate workflows, and we saw a slide thinking within reasoning robots, that Synopsys support a huge budget along with that.

It'll be great to see a vision around that in terms of how you're working with NVIDIA in advancing physical AI. And at the same time, does that mean you're competing with NVIDIA? You're partnering with NVIDIA? How does that whole relationship with NVIDIA work out?

No, that's a great question. Thank you. So the partnership with NVIDIA has 3 layers. The bottom layer is accelerated compute. Any place where we can use GPU to have our products run faster on a GPU. That's the base layer of the partnership. And we've been working with them for a number of years on that base layer. The next layer up is the agentic orchestration layer.

And the third -- the top layer is the physical AI, where we're connecting our Ansys portfolio to Omniverse. Omniverse can be the design platform where it orchestrates multiple technology to envision that future physical robot or a car or a drone. At the end of the day, no one will commit these products before doing tons of high fidelity simulation in order to ensure it's going to be safe, secure in the real uncontrolled world.

That's our role, and that's what NVIDIA saw in the value that Ansys brings into this partnership to accelerate. So definitely, we're not competing with NVIDIA. We're partnering with NVIDIA. Sometimes there's confusion when Jensen or NVIDIA talks about physics simulation. NVIDIA has had physics simulation for a very long time.

If you see the impressive games, the car crashing into a wall or I'm not a gamer, so -- or whatever visualization you see, it looks so real because there's physics simulation in it. But that's not the same physics simulation of -- if you're a BMW and you're building an actual car and you want to do physics crash testing, that's the highest fidelity simulation that Ansys owns in that market.

So that's where it's a complementary partnership. So when you hear that NVIDIA or other, they have physics simulation, it's true. But what we have is the sign-off physics simulation, which is the highest fidelity.

Okay. Since we have a couple of minutes, so maybe my last question, Sassine. You have come up through engineering and sales at Synopsys in decades, and you have seen Synopsys as a leader in EDA for decades right now. And -- but last 12 months have been exciting as well as challenging.

You closed one of the largest deal, Ansys, finally made it happen. We saw some IP challenges, and we saw China restriction there, Intel restructuring, all that. But as you talk about the new Synopsys, new Synopsys, what are the most important things you want investors to take away with about the new signing Synopsys, whether financially, strategically or culturally how -- where you are taking Synopsys to?

Yes. Our mission is to empower innovators to drive human advancement. I've been at the company now for 27, 28 years, and I've been so fortunate to see the company going through multiple stages of evolution and growth. And as you know, you cannot -- and this year, by the way, is our 40th year anniversary. And in 40 years, we've had a number of bumps along the way, but the vision was very clear, how do we continue leading with innovation to drive human advancement, enable our customers with our technology to drive the product that they're building.

Nothing changed there. As you're pointing to the challenges of the last 1.5 years, when we set into the new company, the new direction, we knew we're going to do something very big -- and when you do something very big in an environment with a lot of stress, restrictions on China, changes in the industry, et cetera, we did hit some bumps.

I have no doubt, no doubt that we will continue on leading in the portfolio, both in revenue growth and be disciplined in our financials to have the highest return for our investors and most importantly, for our customers to be dependent and leaning on Synopsys to drive their innovation.

Double-digit growth, margin expansion.

All the way.

All the way. Well, looking forward to the Investors Day in September and looking forward to hosting you again next year at this conference.

Thank you.

Thank you so much.

Thank you. Thank you.

Ladies and gentlemen, welcome to the Synopsys Earnings Conference Call for the Second Quarter Fiscal Year 2026. [Operator Instructions] Today's call will last 1 hour. As a reminder, today's call is being recorded.

At this time, I would like to turn the conference over to Tushar Jain, Head of Investor Relations. Please go ahead.

Good afternoon, everyone. Welcome to Synopsys' Second Quarter Fiscal Year 2026 Earnings Call. With us today are Sassine Ghazi, President and CEO of Synopsys; and Shelagh Glaser, CFO.

Before we begin, I'd like to remind everyone that during the course of this conference call, Synopsys will discuss forecasts, targets and other forward-looking statements regarding the company and its financial results.

While these statements represent our best current judgment about future results and performance as of today, our actual results are subject to many risks and uncertainties that could cause actual results to differ materially from what we expect.

In addition to any risks that we highlight during this call, important factors that may affect our future results are described in our most recent SEC reports and today's earnings press release.

In addition, we will refer to certain non-GAAP financial measures during the discussion. Reconciliations to their most directly comparable GAAP financial measures and supplemental financial information can be found in the earnings press release financial supplement and 8-K that we released earlier today.

In addition, as mentioned in our earnings press release today, we plan to host an Investor Day on September 30, 2026. All of these items, plus the most recent investor presentation and the Investor Day information can be found on our website at www.synopsys.com.

In addition, the prepared remarks will be posted on our website at the conclusion of the call.

With that, I'll turn the call over to Sassine Ghazi.

Good afternoon. Synopsys delivered a strong second quarter, exceeding guidance on revenue, non-GAAP operating margin, and non-GAAP EPS, driven by solid execution and continued AI-driven demand strength.

This is an exceptional moment to be the leading engineering solutions provider, EDA, IP and multi-physics simulation have emerged as essential capabilities in the AI supply chain.

AI is scaling semiconductor demand, architectural diversity and complexity of both chips and the systems they power, driving increased demand across our portfolio.

Our opportunities expanding as customers design increasingly complex systems from silicon to full-scale AI infrastructure and physical AI, requiring more integrated engineering solutions across design, simulation and system validation.

Synopsys is uniquely positioned to capture this opportunity. And our recent Synopsys Converge event showcase the depth of our expanded portfolio and the strength of our road map.

Zooming out, Q2 further reinforced my confidence in our strategy and trajectory. Our global team showed continued strong execution on the Synopsys ANSYS integration, disciplined focus on higher-value IP opportunities and engineering excellence to advance our differentiated innovation pipeline with Agentic AI and multiphysics fusion technology. I look forward to diving deeper on these topics, along with our strategy to increase value capture and expand margins at our Investor Day in September.

Based on our momentum, leadership road map and market signals, we are raising our full year 2026 revenue, operating margin, EPS and free cash flow guidance. I'll cover segment highlights before handing over to Shelagh for the financial details.

Design Automation delivered a strong quarter, reflecting robust AI-driven design activity and sustained demand for advanced node and 3D IC solutions where Synopsys EDA leads. Hardware-assisted verification remained the key growth driver with particular demand from hyperscaler and leading semiconductor customers, who are scaling emulation and prototyping for increasingly complex AI designs. This drove multiple strategic system wins across ZS 5, ZeBu and HAPS-200.

In EDA, our leadership in 3DIC is translating into production scale adoption. For example, in Q2, a leading HPC provider successfully taped out an incredibly complex next-generation AI accelerator using Synopsys' unified multiphysics aware designed to sign off solution. This demonstrates the production-proven capability of our 3DIC Compiler platform, and we expect sustained adoption as next-generation AI designs increasingly moved to multi-die and chiplet-based architectures.

We also continue to lead at advanced nodes with over 30 full floor technical wins in the quarter, driven by our ability to deliver superior PPA for increasingly complex designs.

Across our EDA portfolio, we are extending our competitive advantage by pioneering new capabilities, including multiphysics fusion, GPU-accelerated computing and AI-driven automation. Early results for our forthcoming multiphysics fusion technology demonstrate meaningful productivity gains, including up to 3x faster design closure with higher ECO success rates and up to 2x faster turnaround times for complex analog designs compared to traditional flows. Multiphysics fusion is currently in expanding trials with leading customers and will begin ramping into commercial availability in the second half of 2026.

As we deliver more value to customers, we expect to share in that value creation as contracts are renewed and expanded. For example, we're seeing early signs of monetization with GPU-accelerated EDA, a premium capability driving both increased customer value and contract uplift. We're also advancing a e-driven design. Our Agentic EDA capabilities are gaining traction with 20 customers now evaluating solutions across more than 25 specialized AI agents spanning front-end, verification, implementation and analog flows. This agent engineer technology represents a meaningful long-term opportunity to further increase productivity and drive higher value customer engagements. We are maintaining our EDA leadership position, supported by the success of recent renewals pipeline, activity and monetization trends.

Turning to ANSYS, which delivered another strong quarter. ANSYS extends our reach into system-level design and multiphysics simulation strengthening our position as the leader in engineering solutions from silicon to systems.

In Q2, we saw continued demand for system-level digital engineering and physics-based simulation across industries. For example, the AI data center build-out is driving SNA demand, including and beyond semis as customers use the power of ANSYS simulation from chip to grid. In aerospace and defense, customers are adopting ANSYS simulation to generate physics-based synthetic data to train AI models for highly complex operating environments. And in automotive, manufacturers are increasingly digitizing engineering workflows and relying on simulation for safety-critical systems. Together, these trends reinforce our opportunity to deliver differentiated value at the intersection of silicon, systems and physics.

Turning to design IP. We are increasing our alignment with hyperscaler demand for custom AI silicon, where our differentiated portfolio, first to protocol leadership and silicon-proven quality enable higher-value engagements.

Demand for high-speed interconnect IP continues to accelerate, driven by AI's massive data requirements. In Q2, our PCIe 7.0 IP achieved a greater than 90% win rate with 18 new licenses and a growing pipeline. We also continue to see strong momentum and advanced connectivity technologies, including 224 gig with multiple wins across leading and emerging innovators.

The shift to multi-die and chiplet architectures is driving demand for die-to-die interoperability. In Q2, we secured additional UCIe design wins and achieved a 64-gig tapeout on a 2-nanometer process, bringing total UCIe lifetime wins to over 150. We're strengthening our position in memory IP with design wins across hyperscalers, AI start-ups and leading semiconductor companies. In Q2, we also delivered the industry's first HBM 4 IP test chip.

While we continue to expect muted IP growth for fiscal year 2026, we believe the IP segment bottomed in Q1 and has begun its recovery. We expect sequential quarterly improvement throughout the second half, supported by our road map execution and pipeline. Importantly, we are focusing our IP business on the highest value opportunities, aligned to AI-driven demand and hyperscaler customization. These engagements enable us to provide greater value as they increasingly involve deeper collaboration customized IP solutions and even broader Synopsys participation in the design process.

Also advancing our IP strategy, we expect to close the pending sale of the processor IP solutions business shortly. I'm increasingly confident in the long-term growth of this business and look forward to sharing more at our Investor Day.

I'm also pleased to share that today we announced a cooperation agreement with Elliott Management and the appointment of Jesse Cohen to our Board as an independent director. Jesse has deep appreciation for the company and our mission. We welcome his constructive insights and I look forward to working with him.

In summary, the expansion of AI positions Synopsys for sustainable growth and margin expansion. As AI scales both chip complexity and system-level design requirements our leadership portfolio of engineering solutions across EDA, IP and multiphysics simulation enables us to deliver differentiated value to customers and to capture a larger share of this expanding opportunity.

I want to thank the Synopsys team for an impactful Q2 with disciplined execution, continued technology leadership and engineering excellence driving our next-gen solutions. Now over to Shelagh.

Thank you, Sassine. As Sassine noted, we delivered a strong Q2, achieving revenue of $2.276 billion and non-GAAP operating margin of 39.5%, and non-GAAP EPS of $3.35, all exceeding guidance. The results reflect continued strong execution and financial discipline across the business, backlog ended at $11 billion.

Before turning to the financials, I'll briefly outline the drivers of our revenue outperformance Q2 revenue exceeded guidance primarily due to the strong performance across the business. In addition, an accounting impact associated with recognizing ANSYS channel revenue on a gross basis added $12.5 million to revenue and an equal amount to expense, thus neutral to EPS and cash flow.

Let me provide more details on this change. ANSYS integration is well underway. As we further align and improve our operations, we have deepened our understanding and experience with ANSYS' significant channel partner network by enhancing oversight and pricing visibility, which requires us to recognize channel revenue on a gross basis. This also expands our reach to customers, Synopsys historically did not serve gives us clear business insights and allows us to offer a broader portfolio of Synopsys and ANSYS solutions. We will continue to update you on the quarterly impact through the rest of fiscal 2026 and I'll quantify the estimated full year effect in our guidance shortly.

I'll now review our second quarter results. All comparisons are year-over-year unless otherwise stated. We generated total revenue of $2.276 billion. ANSYS revenue was approximately $652 million, including the accounting impact of $12.5 million related to channel revenue. Total GAAP costs and expenses were $2.156 billion coming in higher than expectations, primarily due to the accelerated timing of restructuring costs. As a result, GAAP earnings per share were $0.09. Total non-GAAP cost and expenses were $1.376 billion, below our guided range, reflecting the progress we are making in improving efficiency and realizing synergies, resulting in non-GAAP operating margin of 39.5%. Non-GAAP earnings per share were $3.35 ahead of our expectations on the strong operational beat.

Now on to our segments. Design Automation segment revenue was approximately $1.822 billion, including ANSYS. As a reminder, this excludes the Optical Solutions Group, which was divested in Q4 '25. Within Design Automation, Q2 EDA revenue grew slightly over 8% year-over-year with strength and hardware-assisted verification solutions. Design Automation adjusted operating margin was 43.3%. Design IP segment revenue was $454 million, down approximately 6% year-over-year and up 12% sequentially. Design IP adjusted operating margin was 24.4%.

Turning to cash. Free cash flow was approximately $575 million in Q2, and we ended the quarter with cash and short-term investments of $2.48 billion. Total debt at the end of Q2 was approximately $10 billion. Based on our strong cash position and our early pay down of term loans, we initiated a $250 million accelerated share repurchase in March, under which we received an initial share delivery of approximately 513,000 shares with final settlement expected by June 1. During the quarter, we also executed a $50 million open market share repurchase of approximately 127,000 shares.

Now to guidance. Given the strong first half results and continued confidence across the business, we are raising our full year revenue, operating margin, EPS and free cash flow guidance. Let me explain further. We are updating our full year revenue guide to account for 3 factors: first, the strong first half performance and increased confidence across the business, increases our previous guidance by $35 million at the midpoint. Second, the ANSYS channel accounting impact increases revenue by $60 million, which is accompanied by an equivalent increase in expenses. And third, the previously announced divestiture of the processor IP solutions business is expected to close shortly, resulting in a reduction of revenue of approximately $40 million for the remainder of fiscal year 2026. This results in an updated revenue range of $9.625 billion to $9.705 billion. Within that, ANSYS revenue contribution is expected to be approximately $2.96 billion, including the accounting impact. This is consistent with prior guidance after including the channel accounting impact.

Next, expenses. We're updating our expense guidance to account for 2 primary factors. First, cost discipline and accelerating synergies driving expenses down. We expect to be approximately halfway through our committed cost synergy realization by the end of fiscal year 2026. Second, a $60 million increase in expenses due to the ANSYS channel accounting impact. Thus, total GAAP costs and expenses are expected to be between $8.469 billion and $8.599 billion. Total non-GAAP costs and expenses are expected to be between $5.675 billion and $5.725 billion and non-GAAP operating margin of 41% at the midpoint, a 50 basis point raise to our previous guidance. GAAP earnings is expected to be between $2.49 to $2.91 per share. We expect non-GAAP earnings of $14.72 to $14.80 per share, a $0.34 increase at the midpoint from our prior guidance due to the higher revenue and increased operational efficiency. We are raising our cash flow from operations guidance to approximately $2.3 billion. Our CapEx guidance of approximately $300 million remains unchanged, resulting in free cash flow of approximately $2 billion, an increase of $100 million versus our previous guidance.

Now to targets for the third quarter. Total revenue between $2.41 billion and $2.46 billion, total GAAP costs and expenses between $2.075 billion and $2.125 billion, total non-GAAP costs and expenses between $1.44 billion and $1.47 billion, GAAP earnings of $0.84 to $0.98 per share and non-GAAP earnings of $3.63 to $3.69 per share. Our press release and financial supplement include additional targets and GAAP to non-GAAP reconciliations as well as full year revenue guidance breakdown outlining the factors I mentioned earlier.

Thanks to our global Synopsys team for a strong first half performance. Our disciplined execution and momentum across the business is a great setup for an even stronger second half. At our September Investor Day, I look forward to discussing the compelling long-term opportunity we have as a mission-critical partner for our customers.

With that, I'll turn it over to our operator for questions.

[Operator Instructions] Your first question comes from the line of Siti Panigrahi from Mizuho.

It's Siti Panigrahi from Mizuho. So Sassine, congrats on a good quarter. I want to ask about the IP business. That's 1 of the questions we get from investors after the weakness last year. It's good to see that Q1 was kind of bottom and sequential improvement. And you talked about some of the shift towards the higher value more customized IT segments with hyperscalers. Can you give us a sense like how these deals are compared to traditional IP? And what other factors you give you that confidence of second half reacceleration and how should we think about the growth opportunity going forward in IP?

Thank you, Siti, for the question. Overall, I cannot be more enthusiastic and confident about our portfolio, in particular, the IP opportunity. If you look at the Synopsys IP opportunity, we have the broadest portfolio serving many markets from AI, HPC and data center build-out to mobile to consumer, automotive, et cetera. And that portfolio is available across multiple foundries. The area that we are focused on, when we talk about high-value IP opportunities is how do we capture the value that you're delivering to the customers and a different monetization and business model. We're making actually very good progress, as I mentioned a number of quarters ago, by the end of this fiscal year, we will have few customers we signed agreements with a new business model that provides the opportunity to capture more dollar than the traditional use fee or some level of NRE. Like the COT the direction and trajectory is built on the availability of the Synopsys IP and that discussion is very positive. I'm confident that we will get to the direction I communicated a number of quarters ago, which will accelerate our opportunity of growth in IP. And as you mentioned, for the short term, what we -- or for this fiscal year, what we committed is sequential quarter-over-quarter growth. And as you could see, we achieved a 12% Q2 to Q1. Q1, we hit the bottom. I have no doubt we'll continue on delivering that sequential growth for the rest of the year.

That's good to hear that royalty update on IP. And Shelagh, I have a follow-up question on your margin guidance you raised for the fiscal year. And if I heard you correctly, you said half of that committed ANSYS cost synergy expected for this year. So can you help us find the magnitude of the remaining synergy opportunity in the back half or in 27? And how should we think about the primary driver for further margin expansion? Any other additional levers you can talk about beyond synergy?

Yes. Thank you for the question. Really, since we finalized ANSYS last year, we've been focused on how we achieve synergies as quickly as possible, as I said. By the end of this fiscal year, we'll have achieved about half of our committed synergies, and we're doing that in a very systematic way, ensuring that we're continuing to invest in building out the multiphysics portfolio. So in making sure that, that's happening and making sure that we've got the right go-to-market resources, but really looking at areas where we have overlap and duplication and reducing those, both in terms of head count and in terms of where we might have had a third-party contract with a vendor combining those contracts. And so we've been working through in a very disciplined way to make sure that we're achieving efficiency in really everything we're doing. In terms of when we'll achieve the rest of the synergies. I'll talk more about that in our Investor Day, but we really do want to get through the synergy work as quickly as possible because we want the teams really focusing on building the innovation going forward.

Your next question comes from the line of Joe Quatrochi from Wells Fargo.

Yes. I was wondering if you could help us just kind of understand of the $35 million increase to the full year guide on the revenue outlook from business performance. How much of that was related to EDA versus IP?

Yes. So we saw strength across the business. The key driver for the strength is the continued AI semiconductor from a chip point of view, opportunities that our customers are seeing and therefore, translating into chip start or a design start and system companies, i.e., the hyperscalers, integrating the silicon or expanding into their own chips, the COT model. For us, it's a great opportunity on both ends on the semiconductor suppliers as well as the hyperscalers because for any of these designs, you will need EDA software you need hardware-assisted verification to verify the chip in the context of the software and IP for any chip start, you need IP. So the strength was across the portfolio. The other part that is actually proving to be increase in demand and essentialness is the SMA solution. Most of these chips are advanced package Thermal is essential, all the physics simulation, like fluid structure, et cetera, are essential. So we're seeing the strength across the portfolio.

And then I guess maybe as a follow-up, I wonder if you can just kind of provide us any sort of color on -- you talked about the engagements that you're seeing on Agentic-AI and agents, how should we think about just the structure of those contracts? And then I guess as we look further, how should we think about genetic AI driving EDA's share of R&D spend higher?

The whole AI for EDA started from the journey on reinforcement learning where we insert AI in every part of our products to a Copilot or an assistant for the human engineer, and we've always talked at some point, the workflow will change toward an autonomous set of engineers or agent engineers, and we're seeing it happening right now. What we're witnessing is the traditional product delivery, where the focus was on the user interface, simplifying out-of-the-box results for the human engineer to manage and pain the complexity of the chips that they are designing to a combination of human engineer and agent engineers running our tools. And that's a fantastic opportunity for us because in both cases, you need more of our products in order to deal with the complexity and the new workflow that our customers are trying to evolve to the current thinking, and we're in early exploration with customers is how do we build from the subscription license that our customer has for the human engineers to run our product to subscription plus consumption for the agents to utilize our products. So that's absolutely an upside for our EDA and SMA business as agents become more pervasive in our customers' workflow.

Your next question comes from the line of Vivek Arya from BoA Securities.

This Liam Pharr on lack of Vivek. So I guess just to start, in regards to your largest customer, it sounds like 18A and 14A pipeline is building. Have you seen any of that benefit? And if not, how and when does it start to impact your numbers?

So the great news for Synopsys is any new foundry or a new technology within the same foundry is a tailwind in particular, for our IT business, because you cannot on-ramp a customer to any technology, process technology or foundry without our IP. It starts with the foundation IP, which is the library, et cetera, and the interface IP. So when we see or you hear about customers like Intel, Intel Foundry, expanding their engagements. We are, of course, aware of these engagements very early on when the target customers evaluating the technology. Now to remind you, we get paid once the customer commits to the technology and they want to go into production during the eval phase is just an eval, once it goes into production, we get paid for it. So in terms of how are we taking it into account for FY '26, we're not accounting or taking into account in our guidance any upside. But as these wins move from an eval into production, we'll absolutely see the upside.

Makes sense. And then for my follow-up, new investors, new board members, what do you expect to change from pricing or operational perspective?

The -- you're referring to Jesse and Elliott. Actually, from day 1, our interaction with Elliott and in particular, in a number of interactions I had with Jesse there was an immediate alignment on the value creation that Synopsys provide the essentialness of our assets. There was no debate on that point. We're passionate about the portfolio and the leadership we have. The 2 other points that they were made, given the value creation and essentialness of the asset, is there an opportunity to monetize further. And the third point, can we improve the efficiency, profitability and translating it into a better operating margin for the company. As we've been talking about for at least 3 quarters now, we see the same thing, you need an inflection point in order to go from that value creation to broader value capture and we're seeing it on the software side with AI, as I mentioned earlier, with the opportunity to have a broader set of users of our technology from human engineer to Agentic engineers. And on the IP side, with the move from a merchant silicon to COT and the essentialness of the IP portfolio we absolutely see the opportunity to change the business model and capture more dollar for the value we're delivering. On the operating margin, there's no debate there's an efficiency as well that we can drive. We are demonstrating it in the last number of quarters. This year, we're raising our operating margin by more than 300 basis points in terms of delivery to where we finished last year. And we see the opportunity to continue on improving on both the top line and bottom line.

Your next question comes from the line of Jason Celino from KeyBanc Capital Markets.

Great. Wow, Sassine, not shying away from tough questions. So for me, I wanted to ask about your IP business. It seems like it was through the trough as you may call it, did you close any business earlier than expected or see some earlier drawdown. So I'm just trying to understand the sequential improvement commentary. Like are you upticking on IP here? Maybe that's my first parter.

Yes. Jason, the current IP sequential improvement is based on the pipeline that we've had and closing the engagements that we could see in our forecast with the existing business model that we have with our customers, where you are seeing a strong confidence and enthusiasm is the engagement around the new business model in particular, in HPC and the AI-based chips with the hyperscalers.

Yes. And Jason, I would just add that as we talked about last time, a part of the sequential is as we move the resources to more fully deploy on HPC, there's title availability that becomes available as we move throughout the back half of the year. And so we need those titles, obviously, to be available for the customers to pull down.

Okay. Helpful. And then when we look at the ANSYS business, it looks like it's growing in the mid-teens, even when excluding the accounting stuff. But keeping the guidance the same for the year, I think the guidance assumes roughly 10%-ish growth. Help me understand the strength in ANSYS and why you're seeing these mid-teens growth levels? And what would drive that steep cell down to double digits in the second half or the full year?

So the 1 thing I'll start with is our very successful integration of the 2 companies. As you know, acquiring a company like ANSYS with a broad portfolio as well as a go-to-market motion making sure we're not missing a beat on both the technology integration as well as the go-to-market. I cannot be more thankful and happy to see that integration coming along. From a market dynamics point of view for the portfolio, there is the semiconductor part of ANSYS, Think of it like the EDA part of ANSYS. And that's where the multiphysics fusion into the portfolio is taking place the number of the engagements with customers with that new technology is happening at a rapid pace with very good outcome. Now the monetization of that is not happening yet because we're in an eval phase with those customers with the new technology. The part of ANSYS that serves industrial, automotive, aerospace and defense we're seeing an uptick. And the reason we're seeing that uptick is picture those products that are being designed for the future. Their intelligent systems, they're very complex, the need for more simulation and analysis to reduce the cost as well as increase the fidelity of delivering to that product is the sweet spot of ANSYS portfolio, because it's the trusted multiphysics simulations for these markets. So that's the tailwind that we are seeing in -- outside of the semiconductor.

And I would -- Jason, I would just add, there's a mechanical aspect here as we closed the acquisition of ANSYS in July last year. We retool them to be on our fiscal year, which means that their December, their prior Q4 is actually our Q1. And so you saw kind of outsized growth in Q1. Our fiscal Q1. And then as we go throughout the year, their reprofile to ours. And so we do see strong growth for ANSYS. It's just kind of got a different seasonality to it. And we anticipate that, that seasonality remains with their strongest quarter always being a Q1 because that traditionally had been there in Q4. So there's a bit of mechanical nature to things, too.

Your next question comes from the line of Gary Mobley from Loop Capital.

Sassine, over the last several quarters when describing chip design activity broadly, you talked about a tale of 2 cities, where in the analog design community, I think you were hopeful you would see some acceleration of chip design activity, but not quite yet. I think the evidence is there in the marketplace that a lot of these big analog chip companies are seeing much improved business environment. So therefore, have you seen sort of a resurgence in that customer base from a renewal activity perspective or just in general chip design activity?

Gary, we track chip start very, very closely. What we are seeing is a chip start increase or a design start increase in anything AI-related. In industrial and automotive, while customers are reporting strength in revenue, there are multiple reasons for that, but the design starts are not growing -- definitely not growing at the pace as we're seeing for the other cohort. Now where we're seeing customers excitement in the analog space is things related to physical AI, because you need sensors, you need actuators, you need the actual analog to interface with the real world and translating it into the digital world. But from a design start is still fairly muted design start activity in that domain.

Okay. Appreciate that color. Just my follow-up, I wanted to sort of get a gauge on the monetization of maybe the half dozen or so joined the collaborated products between Synopsys and ANSYS as outlined at Converge. When would you expect the first phase of that $400 million in revenue synergies post acquisition and then eventually that $1 billion in revenue synergy.

FY '27, because the -- we released 2 limited set of partners, the technology. We're expanding it further as we're getting more feedback and input from the early customers that they're evaluating the technology. And the principle here, Gary, the key principle that we are putting guardrails around with the sales organization and the engagement with customers is 1 plus 1 must be greater than 2. Many of these customers, they have access to Synopsys technology. They have access to ANSYS technology, the new multiphysics fusion it's additive to the baseline. So 1 plus 1 must be greater than 2 to get access to the technology, and that will start in FY '27. We did communicate a $400 million in revenue synergy for that base, the base meaning the semiconductor-related multiphysics opportunity and we -- I want to say, had a thesis that is accelerating around the whole physical AI, digital twin, et cetera. So we're still on track to what we have committed. And actually, the confidence is higher given the early customer feedback that we're receiving.

Your next question comes from the line of Andrew DeGasperi from BNP Paribas.

Yes. I wanted to ask 1 on where you mentioned about the leading HPC provider successfully taping out the next generation of AI accelerator. I'm just wondering, is this like a first 1 in terms of what you've seen from a data center customer? And how meaningful could this be for you?

If you're referring to hyperscaler taping out an accelerator, no, it's not the first one. There are, of course, different hyperscalers at different stages of maturity when it comes to their ability to bring their own silicon inside the data centers. We in each 1 of these engagements, Synopsys IP, hardware, EDA, ANSYS portfolio is in use. And when I say everyone is everyone. There are none of the COT that does not use the EDA, HAV, IP and SNA. The point I'm emphasizing for IP, in particular, as these customers are moving to more sophisticated complex COT, they need to make sure they have a customized IP, the latest IP that is competitive with what they get from a merchant silicon and that's the opportunity we're seeing that is expanding, and I'm very excited about and confident we'll be able to change the current engagement model.

That's helpful. And Shelagh, I just wanted to ask a question on the organic revenue for the quarter. Just given the noise around the channel and also the divestitures, I mean, we're shaking out somewhere between 3% and 4% ex ANSYS. Is that what you're seeing? Or are we missing something?

Yes. I think in terms of the channel piece, you saw us $60 million for the year that included the $12.5 million that was in Q2, and you can think about that growing through the year as we're building with the channel. And so -- and we've talked about IP sequentially growing, which we -- you saw from Q1 to Q2, so we'll have sequential growth. And then really for the balance of the business, it's really timing of when -- because we've had the upfront hardware piece in EDA. So it's really timing between Q3 and Q4 of hardware.

Got it. And referring to Q2 this quarter specifically, is the organic growth accurate?

In Q2, yes. In Q2, it's really the upfront piece. We saw grow, we had a good hardware quarter also in Q2, and then you got the specifics on ANSYS performance, too. ANSYS obviously had the much bigger Q1.

Your next question comes from the line of Joe Vruwink from Baird.

I want to go back to multiphysic fusion, and is the greatest initial applicability really within sign-offs. And I ask because you Synopsys and ANSYS already had very high market share in sign-ups, respectively. But I think the opportunity is probably accelerating at the category level, just given what's happening around advanced packaging. And that certainly brings a lot more sign-off challenges into design efforts. And so is it really a case where the overall pie is starting to grow and to bring together of your 2 companies into this new format. Is it going to capitalize on that?

Yes. Joe, you're absolutely right. The sign-off is always an essential part before a customer commit to the next phase of the workflow. And we're fortunate that we have the sign-off leadership across multiple physics as well as timing, power, et cetera. The opportunity and the innovation we're driving is customers are moving more and more towards 3DIC and chiplet in an advanced package. The complexity of beyond electronics into structure, fluid, thermal, taking these factors into account during the design phase we have the leadership position in 3DIC Compiler and Fusion compiler, bringing that technology in during the design phase, so our customers have a convergent flow, so they're not running into surprises later in the flow is the value we're adding to customers as much as the sign of piece is important bringing some of these algorithm and solvers early in the design phase is the value that we are will engage the customer on.

That's great. And then on backlog, I know that it's just really noisy right now, but the quarter-over-quarter decline to $11 billion, is that as expected? And is it relating to just when renewals happen to fall within the fiscal year?

Yes, you got that right, Joe. It's -- there's a normal ebb and flow we build and then we burn and it's really based on where renewals are and it's very much what we expected.

Your next question comes from the line of Jay Vleeschhouwer from Griffin Securities.

Question for you, Shelagh, first on expenses, then I'll follow up with Sassine for the follow-up. Your head count as of the end of Q2 was down about 7% from the peak at the close in Q3 after ANSYS added about 6,000 or more employees. So it would seem, on the 1 hand that you have a few points left to go to fully complete the RIF that you announced some time ago. On the other hand, what's interesting is that over the last number of months, there's been an unmistakable sequential uptrend in your open positions for both Synopsys classic and ANSYS classic. As an example, Synopsys classic positions are more than 4x the number at the end of Q4, ANSYS classic more than double where they were a few months ago. So maybe talk about what you're thinking of with respect to bringing people in as per those numbers versus, on the other hand, reducing your head count to keep the margins in line? Then my follow-up.

Yes. And so you're right, Jay, we still have some more productions to go for our 10%. So as we had said, we're doing that through the course of the year. So there's still some more actions that are taking place. But at the same time, we're also investing in critical areas and making sure that we've got the right technical folks, both in the go-to-market and on the engineering side to deliver the road map that Basin has been talking about. So we are doing a mix of reducing in areas that are not priorities for us while we are investing in key priorities for ourselves. And we're being very disciplined about the roles that we're hiring for. And it's really about building the road map out and then making sure that we've got the right robust go-to-market team to be able to support that. But we are still committed to the 10%. You're right. We've done a majority of the reduction. So what we have left to go is a bit more measured. But nonetheless, we're still investing and making sure that we've got key critical technologies funded properly.

Understood. Thank you. So seeing the accounting thing with regard to the ANSYS channel is interesting, but I am more interested in the operational plans that you have for that channel. In ANSYS' last year, it was a more than $600 million business overwhelmingly not EDA. The first batch of the multi fusion cohort is largely about EDA integrations, it probably would have happened anyway. So could you talk about what the product set has to look like beyond this first batch in multiphysics to really enable you to sell more conjoined products into that answers channel beyond just the EDA products? And then maybe speak more broadly about what your new CRO has been doing over the last half year?

Yes, Jay, your observation is correct. The ANSYS sales channel had the direct the sales organization had the direct sales and the channel. Most of the EDA were handled with direct, very little was handled in the channel. So the semiconductor customers and the customers that they are classic to Synopsys and the multiphysics fusion, that will continue on happening primarily through the direct channel. And in most of the direct channel is the Synopsys classic channel, where we have integrated the ANSYS EDA into the Synopsys classic go-to-market team. There's some cross-selling opportunity with some of these customers, and that's what Mike, the CRO is working on and ensuring that there is a smooth interface to the customers. So far, actually, I've been very pleased with the way that integration is going from a go-to-market point of view. Then you have the channel partner that ANSYS has built over decades, which is truly impressive. The ability to go after long tail of customers and capture the opportunities is something that the classic synopsis would like to leverage in areas of the portfolio that we did not have the similar investment or coverage. So we are moving some products from the classic Synopsys into the channel in order to just do what they do best, engage with customers in a light touch and broadly to sell that portfolio. Mike, as you know, brings in a very strong knowledge of both EDA semiconductor and has a very strong view and experience in the whole system level design and the whole industrial, automotive aerospace from just the fact where he came from. So he's been very deliberate on architecting the organization to deliver the current as we're building the future opportunities.

Your final question comes from the line of Josh Tilton from Wolfe Research, LLC.

I've never sounded so official in my life. I have 2. The first 1 is more of a clarification question. I was just hoping that you can maybe help us unpack some of the strength you saw from a geographic perspective, China was up sequentially but North America and I think Europe declined. So anything to call out on what kind of drove the dispersion there? And then I have a follow-up.

No, overall, actually -- I'll comment on China first, but then the rest of the regions is there are no surprises per se. And even with China, there isn't much in terms of change from what we've communicated before. where the design start environment in China remains challenged given all the restrictions and the cumulative impact of the restrictions. And as we've communicated, we're fairly pragmatic when it comes to our guide in China. As far as the U.S., Europe, et cetera, where we are seeing strength as outlined in our S&A portfolio, a number of areas outside of semi, like aerospace and defense, automotive, industrial and that's happening across the board.

And on China, in particular, that did show strong growth, and that's also the addition of ANSYS because we didn't have ANSYS. And then it's also -- it was a pretty easy compare versus Q2. So we haven't changed our -- anything in terms of our forecast of China for the year. We're continuing to be pragmatic about China.

Makes sense. Maybe just a follow-up and a very high level on kind of stepping back. I think a lot of investors listening to this call and either myself kind of look at Synopsys and see a whole laundry list of reasons as to why we are all hoping and bedding and looking to a future where we think growth can be better, whether it's pricing on multiphysics fusion, the IP business recovering, genic opportunities new hardware like the list is endless. But Sassine, when I listened to you in the prepared remarks, it felt like you used the word durability of growth, a lot more than kind of this talk track around improving growth. And I'm just kind of curious, I don't want to run what you're going to give us at the Investor Day, but just like how do you think about the potential for Synopsys to improve the growth rate from here versus more of that durable type of growth you were talking to? Anything you could just help us understand maybe the shape or just how you're thinking about the future growth power of the business given that whole laundry list of opportunities that kind of just rattled off. That would be great.

Yes. Thank you, Josh. The part I want to emphasize is there's a beauty about having the durability of the business. But at the same time, there are a number of inflection points. You just -- as you said, rattled a number of them, the few I outlined that there is commitment focus, discipline in changing the monetization capture is around IP is around EDA and SMA when it comes to the inflection point with AI. We're not expecting the customer to pay more by just delivering the same. But as they are injecting a change in their workflow with agents, with collaborating with humans and there's a massive increase in demand for licenses to train and influence these agents. We are absolutely expecting that the change in monetization and business model will happen, and we will drive it and we'll make it happen. That's what I'm really looking forward for the Investor Day to share with you all how are we thinking about it? And this is not something new. We started thinking about it in the last couple of months. We've been talking about it for a number of quarters that we are determined. Given the value we're delivering and creating, we will capture different value and different business model to drive it home, and we'll talk about it more at Investor Day.

And I know that out of time with that, I'll take the opportunity to just really wrap up with my enthusiasm to be the leading provider of engineering solutions from silicon to systems. Our portfolio spanning the EDA, IP multiphysics simulation are all essential for the AI innovation. A huge thank you to our global Synopsys team for an amazing quarter and thanks to our customers, shareholders for your continued commitment. Thank you.

This concludes today's call. Thank you all for attending. You may now disconnect.

Good morning, everyone. I think it's still morning, and welcome to San Francisco. This is the TMT Conference, Morgan Stanley 2026, and I'm glad to welcome to the stage, Sassine Ghazi, CEO of Synopsys. Sassine welcome.

Thank you.

Maybe just to help level set everyone. Maybe -- it was only just last week, we did the results. So maybe you could just help us summarize what it was you highlighted for Q1 results, what you said for Q2, and maybe a little bit about the '26 guide?

Great. Before I go into the Q1 and the year, it's important to point out that FY '26 will be the first year that we have the combined companies, Ansys plus Synopsys coming together. And that provided a significant expansion for the opportunity that we have.

Synopsys has gone from a silicon design solution to silicon to systems engineering solution. And the timing could not be better for these two companies to come together as you look at the opportunities of physical AI. You look at the complexity of chips that needs to go into these systems, the holistic approach of designing these systems from silicon to system becomes essential.

We delivered solid Q1. We said what we're going to do, and we did it. And we delivered on the revenue towards the top line of the guide. We beat on EPS. We reiterated the guide for the year. So it's a great start of the year and gives us confidence to the guidance that we provided.

Got you. I made one mistake. I should have read the disclaimer at the top. Even if we just do that now, and we'll pretend we didn't do that. Today's discussion may contain forward-looking statements related to our current outlook, expectations and beliefs, which are subject to certain risks and uncertainties that could cause actual results to differ. Please refer to Synopsys most recent SEC filings for a discussion of risk factors that may materially affect these statements. Sorry about that. Back on track.

So maybe just with all that's being said, now with the integration of Ansys, what is driving the growth as you look across the group? It looks to be from the outside. So IP and hardware are part of that growth. But how do you see things this year?

Yes. Again, if you zoom out and you look at where are the opportunities from a market point of view, the complexity of designing the more sophisticated chips for AI applications require deeper integration, or what we call co-design, co-design between electronics and physics. That's one area.

The second area is as you envision the world with many companies trying to invest and deliver to more intelligent systems, be it a car, a robot, drone, et cetera. How do you design these intelligent systems by reengineering the way that you engineer these systems, creating a digital twin, be able to reduce the cost, et cetera. So that's the second area.

The third area is around agentic AI. It's such a great opportunity to attain the complexity of how these products are designed. So when you think of the electronics and physics core design, Synopsys with the new portfolio will be leading with having the physics sign off, be it thermal structure, et cetera, come into the design phase of the silicon. Actually, next week, we have our conference called Converge, where we'll be announcing a number of the joint solutions across these 3 vectors with the digital twin as long as the agentic effort that we're building.

Got you. Maybe if we just stay with the agentic effort, as you've outlined here. It does look as though you are starting to see a little bit of a competitive advantage coming to yourselves relative to some of the peers. And I think on top of that, there's been some sort of suggestion that this will be value-based pricing.

Maybe help us understand how could that be done in practice? Where are you seeing customer interest arising? And maybe the time line as well for [indiscernible].

The way we thought about AI is to tame complexity of the work our customers' R&D is dealing with. So we started an investment in 2017 around reinforcement learning. And we inserted the reinforcement learning in every opportunity we have into our product portfolio. We started selling that solution around 2020 time frame with a similar business model as we've had for EDA, which is a license consumption based.

The next wave was generative AI. With generative AI that really changed the user interface, the way the user deal with our technology. Because our customers are dealing with very sophisticated complex problems they're trying to solve, how do we ramp up new engineers, or how do we make the existing engineer more efficient? So think of it as an assistant for the engineer with generative AI.

A year ago, we announced our vision and road map for agentic. We think of it as a series of task agents, or AgentEngineers, with a cognitive layer that you can orchestrate around these multiple AgentEngineers to change the workflow. The monetization opportunity and the new business model, we don't believe will happen unless the workflow will change. With agents, it will change the workflow. When the workflow changes, you're not counting anymore how many licenses am I consuming, and am I signing a 3-year agreement on prem to get access for these licenses? The delivery mechanism is very adaptive because those models are going to change at a much faster rhythm than the traditional software that we release every 9 months.

Most of our customers run that software on-prem today, then there will be a layer of that -- once you move into these AgentEngineers that you need access to more compute. So therefore, a cloud model. And the outcome is going to be significant improvement to the time to get to results and the quality of the results. So that's the opportunity where we see the workflow will change, then the monetization opportunity will be different.

Okay. So the workflow here as far -- when you say workflow changes, do we see steps being shortened materially? Is it optimization on certain like place and route, for instance? How does it all work?

So if -- let me describe it in -- at the semiconductor chip design, as well as the simulation and analysis because they have different user persona and a workflow that you need to think through.

At the chip design, the chip design is multiple parts of that workflow. You start with the requirements, and you start really the chip design very much as a software entry point. Then you go all the way to the last phase, which is process technology manufacturing physics-based. Because if you're going to manufacture, say, at TSMC, or Samsung, or Intel, or GF, or whomever, you need to make sure that you have the physics representation of the process technology taken into account during the first phase of the chip design.

So the workflow has multiple steps. Some part of the workflow, the agents can do a great job to augment the human engineer and take on certain tasks to make the engineer more effective and efficient. Other part of the workflow is a better quality of outcome of results faster. Some part of the workflow is very difficult to bring in an agent to take on the task. Other part of the workflow and agent will be a perfect fit. So the way we mapped it out last year, they're going to be L1 through L5 in terms of levels of maturity for agents. From a task agent to the orchestration, et cetera.

Today, we are delivering a number of tasks, agents or AgentEngineers with some sort of a cognitive layer to orchestrate these agents, and we're in early adoption with customers to see. What is the impact overall on the time to design the chip, and the quality of the chip. Because with the objective to improve the power or the performance, or the cost of the chip. So when we think of a workflow, it's -- in the chip design, it's a series of tasks and which task can be at this stage delivered to an agent to deliver to it.

And simulation and analysis is slightly different. In simulation and verification in general, it's all about how much verification can I get done in the fastest and shortest time possible because there the bottleneck is time. AI is a great opportunity to accelerate. And we're working on a number of other investments besides AI. There, for example, compute acceleration like GPU is another opportunity where, for example, a fluid dynamic simulation can be accelerated by 100x, 300x. That's a significant improvement on a task that may take weeks that you can reduce to days or hours.

Yes. Incredible. A hundredfold increase. So maybe if I just try and just quickly summarize there. You're talking about various optimal points across the entire flow. The flow itself could introduce different agents, maybe multiple agents across the flow. And then there is a difference between the EDA flow, obviously, and what you're doing in simulation analysis. But there -- and you did talk about verification. And there is, maybe, a concern in the market that some of the coding that's done, pre-verification will go to RTL, for instance, could be done utilizing models at customers. And yet you have tools that have got decades of data algorithms behind them and data layers. So how do you deal with that competition, that potential risk in the market?

Yes, they are part of the workflow. They are very similar to a software development. You write code. That part of the business is very, very small because our customer owns writing that code. Not Synopsys is trying to write the code for the customer or -- the tool we provide, once you write that code is it going to be functioning. And as you go deeper into implementing it into physics, are you able to manufacture it. So it's not a code that you write and you say, okay, that performed the task, I'm done. There's a physics element of it. The code that is written needs to be physically implemented and that physical implementation is still using software. Then once you go into the manufacturing step that you need to make sure you have the physics of manufacturing taken into account when you're implementing that physical implementation.

Those are series of complex solvers that we have built over decades. In collaboration with the manufacturing technology and the architecture level. We are -- when we talk about agents, engineers and tasks agents, we are leading with the disruptions that we say with AI, there are certain tasks that how do we leverage the solvers that we have with the cognitive layer or any foundation LLM, that is out there and provide a new better solution for our customers.

So we -- I don't want to take the thunder out of next week as we're at Converge. But when we talk next week about the series of advancements we've made with these AgentEngineers is quite remarkable. And the reason we have the advantage is because we own the solvers. And our customers from a data point of view, et cetera, we have that entire visibility to build these agents.

Yes. And so ultimately, the AgentEngineer will call the solvers, the underlying software tools. So you get a much more deterministic outcome for the client?

Exactly. And then the next phase is when you have an orchestration of these multiple agents. That's where the workflow will change.

Got you. Okay. Maybe just changing to the new NVIDIA relationship that you guys talked about a month or so back. And trying to understand the sort of commercial traction for Synopsys here. Time lines to use the work that you're going to do around Omniverse. Maybe just help us understand how does that work? How do you monetize this? And when does it all happen?

There what triggers -- so we've been a partner with NVIDIA for decades. And what triggered that deeper partnership is really the expanded portfolio. When you look at the Synopsys portfolio, historically has been targeted and focused to semiconductor companies. The companies they're designing chips. As these chips are sitting in a very complex system, be it a data center or a car or a humanoid, et cetera. In order to achieve the best total cost of ownership of these end intelligent systems, a lot of customization is happening. That's where you see a plethora of architecture ASIC customization, COT happening with these end system companies.

The complexity of thinking of the system as a stack from silicon to software and to the system level, the end product level is a complex engineering task. And today, the way our customers are trying to differentiate is how do they reduce margin and improve the cost across the stack. With the Ansys portfolio, we're very uniquely differentiated because we own the physics simulation with the design of the silicon. NVIDIA could see that. They could see that as they're designing themselves a system, and as they're trying to capture the opportunity of the future, we have a massive workload for engineering.

So today, you cannot think of any type of engineering, be it mechanical, electrical, electronics, et cetera, that is not using Synopsys one way or another. Most of these workloads are running on CPUs. Most of these workloads need to be accelerated. So the closest opportunity to accelerate is a GPU. We have a road map that we are committed to deliver with the joint R&D with NVIDIA by the end of this year. And we have some proof points of number of technology that we have invested prior to that announcement with any -- with a range of anywhere between 10x to 20, 25x improvement to a CPU. That's a great monetization opportunity.

So what the customer will see is from many weeks to fewer weeks or days that are -- they're willing to pay extra money and value for that acceleration. That's one layer of the collaboration is the GPU acceleration. The next layer of collaboration is the digital twin of these intelligent systems. With Omniverse, as the -- think of it as the cockpit to bring in an end product requirements, and before you go into the manufacturing of that product, you need to validate. Will it function in that simulation world? In the physical world, in the real world? So you need an accurate physics simulation in order to go from that digital design to the physical design.

And again, this is where the Ansys portfolio today, if you think of a car or an airplane engine, or any applications a drone, robot there are mechanical aspects that are driven by electronics, that you need to make sure you have the right -- either gas or electric battery mileage. You have the right fluid dynamics to improve the efficiency of the product, et cetera, et cetera. And this is where the Omniverse partnership is about.

Perfect. It sounds very exciting, actually. So we look forward to March 11 was the event?

Yes.

Superb. Maybe if I take you back to, however, Q3 last year, we did see a couple of issues come up, which do look like they're now going into a rearview mirror. One of which was in China. Maybe you could help us understand again, it did seem as though IP in China was getting something of a roadblock and there were some road map issues going forward.

Can you just maybe outline what was happening there? And if indeed China as a growth story in IP comes back for Synopsys?

Yes. So let me describe China then IP as both separate and how did they impact one another.

China for a number of years was a very fast-growing market for Synopsys, primarily driven by the number of start-ups. If you go back to 2019, 2020, '21 time frame, the number of start-ups in China doing chip design, were at a pace much faster than any other region in the world. That was a fantastic opportunity for Synopsys, not only driven by IP, driven by IP and the rest of the EDA portfolio.

Then what we've seen over that period of time since then, the number of start-ups are shrinking. And there's the headwind coming from the cumulative impact of restrictions on technology in China. The impact on Synopsys was more significant than our competitors because our position and IP in China was much bigger than any peer that we compete with in China. So that's the China dynamic. So what we communicated for FY '26, we are derisking China, meaning we're assuming the environment in China will not change. So that's the China aspect.

Now from an IP portfolio point of view. We have the largest in terms of breadth of an IP portfolio that serves multiple markets. So today, if you are a semiconductor company designing for automotive, for industrial, for mobile, for HPC, Synopsys is your partner of choice. If you're designing on TSMC, but the next chip is on Samsung, Intel, GF, we have our IP available on all foundries for various markets. That has been our business for about 25 years on IP. So you build it once, you sell it many times, and you provide the IP before the customer needs the IP.

The trend over the last 3, 4 years, especially with AI-driven semiconductor chips is a lot of customization of that IP, and that's where you see companies like Broadcom have been benefited greatly from customization in ASIC. And then you see many of these hyperscalers designing their own chips in order to improve their TCO for specific workload. That's a fantastic opportunity for Synopsys, but it's a change in opportunity, meaning we still have to deliver on that broad portfolio that you build it once, sell it many times. And we need to build a new lane of customization for these opportunities.

So what we communicated is for that new lane of opportunities, we have to approach it with a different business model and with a different approach with these customers. Because if you take the top 1 or 2 ASIC companies out that they have their own IP, the rest of the ASIC companies rely heavily on Synopsys for their business. They cannot have an ASIC business if we don't have our IP business. So they're very open to adapt to a new business model.

And same thing with hyperscalers. As they're building COT, they're building an IP group. They need the IP to come from Synopsys, but we need to customize it. So when we talked about FY '26 will be a transition year for IP, is for us to continue on serving the current business model and market. And as we adapt and allocate resources and investment to serve that new opportunity.

And that adoption of IP business model. If I remember right, you used the word pivoting to subsystems as a design, which seemed like as though you were dancing close to the idea of making chiplets or custom designing chiplets for perhaps ASIC players or hyperscalers. Is that the right way to see this going forward? And do you see this as a bigger TAM of dollar capture for you guys?

Our customers are pulling us in that direction. And by the way, when I say customers, in this case, are the HPC customers, the hyperscalers and the semiconductor companies building to serve that cohort of customers. We've been evolving from delivering an IP as a stand-alone small block to a bunch IP working together that sits on a bigger part of the chip. We have been down that journey for a number of years now.

But what we're trying to change is the monetization of that work. Because the way we sold IP is, you buy the IP for one use on a chip. The next chip, you buy the IP again, the next chip, you buy the IP again. It's been very healthy and great business model. Now with the customization, you have a use fee plus an NRE. But given the demand on the resources, and these are scarce resources, we need to have a use fee in NRE plus some sort of a share. Think of it as a royalty for these engagements. And that's the period we're in right now. We're in a number of discussions with those customers to pivot to a new layer of monetization for that resource investment that we're making.

But we're not going all the way to build the chip. And the reason we're not is because we are an ecosystem. The moment we decide to go all the way to build a chip, then we're competing with the whole slew of our customers. I would rather sell to many, many, many of those customers and monetize better, versus building and competing with the customer.

Got you. Okay. So there's still value to be had coming in and enabling subsystems for customers utilizing resource to get there and then taking a royalty in the market afterwards?

Exactly because in this model, we can engage as an ecosystem to many of either the ASIC, or chip companies that are serving that market, or the hyperscalers themselves that they're building that chip.

Got you. Okay. Maybe if we turn to foundational IP, and I think you're #1 customer there was -- there wasn't a pull down on their customers at a certain process node. And the suggestion, I think, from yourselves had been maybe just look at that as potentially a 0 for this year, the foundational IP from the #1 customer. Is that still the right way to look at this? And how about foundational IP as a general opportunity for the next 2, 3 years?

So by the way to -- from a terminology point of view, there is the foundation, but we have two categories of IP. We have a foundation IP and an interface IP. So think of them as both are needed to work with a foundry in order to on ramp customers on their node and technology. What we said is for that particular foundry customer, the way we're approaching FY '26 from a guide point of view, we are assuming that there will be no new design start with that foundry customer in our guide. If there are, great, that will be an upside. But we're derisking it from a guide point of view.

Now you can argue you're being pragmatic with that approach? Yes. Why? Because we have the transformation of the IP opportunity, as I just described, that we need to make sure we capture it as well. From the long term, the opportunity for IP is massive. For all the reasons I mentioned earlier, if you're building a chip and you don't want to just buy a general purpose from whomever you're buying the general purpose chip for to -- for your data center, and ASIC, you're limited to very few players. You want to build either your own chip or work with a broader set of ASIC companies to customize the chip for that third cohort. You cannot get to it without the Synopsys IP. And that's the opportunity that we want to capture and make sure we have the resources and the investment allocation for that market.

Got you. That makes sense. One more from me and then I'll open up to the floor. Just on Ansys and the integration now. It seemed as though on the call last week that you pulled forward some of the synergies, the cost synergies, maybe to next year, but possibly even this year. Is that the case? And can you maybe help put some numbers around that for us?

Yes. Actually, it was -- by the way, thank you for bringing this point because it's -- it does require some attention to share with you the strength of our balance sheet. We had short-term debt to be paid off over a 3-year period. We ended up accelerating it and paid it off in 6 months. So that tells you the strength of the balance sheet we have of the position that we have. So yes, that was paid off from a short-term debt point of view.

And actually, just Monday yesterday, we have announced $250 million buybacks with -- again, that we believe it's a great return given where we are from a market point of view. The other priority that we're driving, we said there will be $400 million in cost synergy that we'll achieve in 3 years post the Ansys acquisition. That is being accelerated as well. We have confidence that we'll be able to accelerate and achieve the $400 million in cost synergy much earlier than the 3-year point that we set initially.

Perfect. Maybe I will open up to floor at this point, see if there's any burning questions. I've got one down here.

Thank you. Sassine, more of a near-term question, but one of the concerns that analysts are expressing is around just the core EDA growth slowing from the high single-digit range, even while we're seeing all this strength in AI compute demand. So I guess my question is, why would EDA -- the core EDA growth be slowing in this environment?

Yes. So thank you for the question. How do we monetize core EDA? Either our customers are investing more in R&D, and we get the percentage of that increased investment or they have a need to use more of our new technology. New technology, be it the GPU acceleration, the joint solution with Ansys or the AI technology, et cetera. We have a great monetization happening today in EDA for that cohort of customers, what we call it the tale of two markets today that we're selling into, that are investing more in their R&D, and they are adopting the latest technology to tame the complexity they have.

But if you look at the broader semiconductor market, there is still a big chunk of companies that are not investing more in R&D, and they're not facing forward in their road map. Net-net, when you aggregate these two, this year, we're going to be delivering close to a double digit for EDA. But the long-term confidence in EDA as double digit, same thing with simulation and analysis at double digit, as IP in the mid-teens remain given the need for that sophisticated silicon that our customers are building.

Yes. Thanks for that question. Maybe just staying on that, I mean...

I think there is a question right there.

There was another one there? Sorry.

Just following on the same question. I was curious, given the market structure that exists in EDA, why do you limit yourself to the R&D budgets of your customers? Why not think about their revenue, their demand equation, and try to tap into that value creation? Versus say, okay, if I'm customer A and I set my R&D budget at X, well, I hope to get a percentage of that. When clearly, those customer companies are tapping into a demand equation that is massively accelerating?

On the EDA side, the percentage of R&D dollar that's coming to Synopsys and our industry has been increasing. Due to complexity, due to -- primarily complexity of what our customer is doing. Where we're seeing the opportunity to capture exactly what you're saying is in IP. And IP is exactly what we're positioning that change in the business model from the historical 25 years of just the use fee to capture the dollar amount.

That if you look at percentage of R&D that the EDA used to capture about 10 years ago, it was in the single digits, 7-ish percent or so, where right now is close to 12%, and that budget of R&D is increasing. The change in the workflow is the new opportunity to change the way we capture value for the impact we're delivering to the customer.

Maybe we've got one down front.

I guess your EDA business is fundamentally a SaaS model. So the question is, are you yourself vulnerable to AI disruption?

It's not really a SaaS model. Today, the -- its license based that is on-prem primarily. So the way our customers today, they assess how much money do they spend with us is based on their number of engineers and the tasks they are running. So in many cases, you have an engineer running many, many licenses and other parts of the workflow, one engineer is running very few just because of the interaction and part of the workflow.

As far as the AI impact, AI is a great opportunity for us. It's actually driving the opportunity to monetize more. I mentioned earlier, reinforcement learning, et cetera, those are techniques that we have product and we're monetizing. And remember, what we deliver, it has a software layer that is driving deep physics, solvers and engines that we do. Therefore, the AI opportunity to improve the user interface with generative AI, et cetera, we are leading with that innovation to our customers. With the next opportunity of agents, we are leading in building these agents with the solvers that we have. So we see it as absolutely a tailwind to simplify what our customers are trying to do, which is very complex already, both at the silicon level, as well as the system level.

Great. I see we're out of time. Sassine, thank you very much.

Thank you so much. Thank you.

Thanks.

Ladies and gentlemen, welcome to the Synopsys Earnings Conference Call for the First Quarter Fiscal Year 2026. [Operator Instructions] Today's call will last 1 hour. As a reminder, today's call is being recorded. At this time, I would like to turn the conference over to Tushar Jain, Head of Investor Relations. Please go ahead.

Good afternoon everyone. With us today are Sassine Ghazi, President and CEO of Synopsys; and Shelagh Glaser, CFO. Before we begin, I'd like to remind everyone that during the course of this conference call, Synopsys will discuss forecasts, targets and other forward-looking statements regarding the company and its financial results. While these statements represent our best current judgment about future results and performance as of today, our actual results are subject to many risks and uncertainties that could cause actual results to differ materially from what we expect. .

In addition to any risks that we highlight during this call, important factors that may affect our future results are described in our most recent SEC reports and today's earnings press release. In addition, we will refer to certain non-GAAP financial measures during the discussion. Reconciliations to their most directly comparable GAAP financial measures and supplemental financial information can be found in the earnings press release, financial supplement and 8-K that we released earlier today. All of these items, plus the most recent investor presentation are available on our website at www.synopsys.com. In addition, the prepared remarks will be posted on our website at the conclusion of the call.

With that, I'll turn the call over to Sassine Ghazi.

Good afternoon. We're off to a strong start as we enter our 40th anniversary year with an expanded portfolio leadership positions across the business and the most compelling road map in our history.

In Q1, we achieved revenue at the high end of our guidance and non-GAAP EPS exceeded guidance. 2025 was a year that transformed the company. 2026 is the year we begin delivering on the technology promise of Synopsys plus Ansys. Let me take a few minutes to address market trends shaping our opportunity and provide some highlights from the quarter. After that, Shelagh will take you through the financials in more detail. First, the market trends, starting with AI. We continue to see a tale of 2 markets. On the one hand, the multitrillion dollar AI infrastructure build-out continues unabated, that's driving system level and semiconductor R&D with continued robust design start activity for AI compute. At the same time, design starts in markets like consumer, automotive and industrial remains subdued despite signals of modest recovery. AI's rapid progress is also prompting healthy debate about whether it will disrupt established software companies.

Let me explain why we're different. Our deep tech solutions power the world's most complex engineering efforts. Synopsys decades of deep domain expertise, proprietary code basis and solvers and native foundry design technology co-optimization, deliver optimal, deterministic, silicon-proven results that probabilistic AI models do not replicate, while AI will transform engineering software, Synopsys is already leading that transformation. We're pioneering AI-driven design capabilities in our products that deliver orders of magnitude, productivity gains for our customers and pave the way for agent engineers with increasing levels of autonomy.

One highlight among many this quarter were receiving World Economic Forum honors for our work with AMD to advance AI accelerated chip design. AI isn't disrupting our business. It's amplifying our strategic advantage. Another market trend and tailwind for Synopsys is the engineering transformation away from physical testing towards digital wins to build smarter, more connected products at pace and at scale companies are investing in advanced design automation, simulation and digital twins as a competitive imperative. There is incredible demand for silicon to system solutions that can enable holistic software hardware co-design to accelerate, derisk and reduce the cost of building AI-powered products. Our combined Synopsys plus Ansys portfolio is increasingly mission-critical to the innovation of industries spanning semiconductors, aerospace, mobility, energy and advanced manufacturing. We'll have a lot more to say about this in a couple of weeks at our Synopsys Converge Conference.

Turning to Q1 business highlights. The global Synopsys team executed well. against the backdrop of continued geopolitical and macro uncertainty as China headwinds persist. Let me share some segment highlights from the quarter. First, design automation. We saw continued strength in hardware with major competitive wins at both new and existing customers. including a marquee emulation win versus the incumbent at a leading AI HPC customer. With growing demand for software-defined, configurable systems supporting both emulation and prototyping as well as a strong 2026 road map we are well positioned to capture the expanding digital twin opportunity across industries. In EDA, we also saw sustained momentum across 3 trends: first, the application of AI across the stack. Major semi and hyperscale customers using Synopsys.AI have seen up to 50% faster knowledge assistance, up to 70% faster workflow assistance and up to 5x faster formal test bench generation. Our agent engineered technology is advancing rapidly, and we have several customer engagements underway with agents across design and verification.

Second, leadership in multi-die. Multi-die momentum accelerated as leading semiconductor and foundry customers adopted Synopsys' 3DIC Compiler platform. leveraging automation and AI-driven optimization with our industry-leading multi-physics analysis tools to improve signal and power integrity quality of results enhance thermal efficiency and speed up design convergence. And third, sustained design win momentum at advanced nodes with our digital flow including Fusion Compiler and PrimeTime achieving 100% usage on critical tape-outs at 2-nanometer and below.

Moving to Ansys, which delivered a strong Q1 performance driven by robust demand for system level, digital engineering, multi-physics simulation and AI-enabled design flows. We won large multiyear agreements across aerospace, hyperscale, industrial and automotive. With Ansys as part of Synopsys, we now support more than 90% of the top 100 automotive suppliers. And at CES, in January, we showcased how AI-driven simulation is helping customers like Audi, reduce physical prototyping and shortened development cycles. Our confidence in this business is only increasing as global demand for electrification, autonomy, digital twins, advanced semiconductor design and mission engineering remains resilient and expanding.

Turning to design which performed in line with expectations. As we've said, 2026 is a transitional year for the IP business and we're focused on aligning the fastest-growing segments of the silicon market. We're making progress on this front. The planned sale of our processor IP solutions business to Global Foundries sharpens our focus on extending our leadership positions in interconnect and foundation IP. As interconnect standards evolve at an unprecedented pace, customers count on Synopsys, one generation ahead approach. And in we saw continued strong demand for high-speed protocol IP. We achieved more than 40 PCIe design wins in the quarter with HPC and automotive customers. achieved an industry-first demonstration of PCIe 8.0, and established first-to-market position with our 224 gig SerDes on advanced nodes and leading foundries with 10 lifetime wins.

We continue to expect muted FY '26 growth in with sequential improvement given our road map and sales pipeline. Longer term, several industry trends give us conviction in the growth trajectory of the business. This includes the global expansion of foundries and accelerated node transitions, standards advancing at unprecedented pace and increasing demand for chiplets and subsystems. Our 4-year anniversary year is off to a great start with operational excellence, financial discipline and the most competitive compelling road map ever. Our priority for FY '26 remains on driving sustainable growth and margin expansion by advancing our technology leadership with holistic integrated silicon to system engineering solutions by pioneering a e-driven engineering and focusing our IP portfolio for growth. And efficiently scaling to accelerate our strategy. The access integration is well underway. It's great how our teams have come together at pace to solve engineering's biggest challenges. We'll have a lot more to say and show at Synopsys Converge in March, and I look forward to seeing many of you there.

Now over to Shelagh.

Thank you, Sassine. As Sassine noted, Q1 '26 marked a strong start to the year with revenue at the upper end of our guided range non-GAAP operating margin of 42.1% and non-GAAP EPS above guidance. These results reflect strong execution and financial discipline across the business. Backlog ended at $11.3 billion, underscoring our strong and resilient business model. As a result, we are reiterating our full year revenue non-GAAP operating margin and cash flow guidance while raising our non-GAAP EPS guidance for the full year.

I'll now review our first quarter results. All comparisons are year-over-year unless otherwise stated. As a reminder, our Q1 '25 compares include the Optical Solutions Group, which was divested in Q4 '25. We generated total revenue of $2.41 billion coming in at the high end of our guidance, primarily due to the timing of Ansys deals. Ansys revenue was approximately $886 million, reflecting our leadership simulation and analysis portfolio and exceptional execution in the seasonally strong quarter. Geographically, China grew approximately 21% year-over-year due to the inclusion of Ansys. Excluding Ansys, China revenue declined slightly year-over-year, consistent with our outlook. Total GAAP costs and expenses were $2.2 billion, Total non-GAAP costs and expenses were $1.4 billion at the low end of our guided range due to timing, resulting in non-GAAP operating margin of 42.1%. GAAP earnings per share were $0.34. Non-GAAP earnings per share were $3.77, coming in ahead of expectations on revenue and expense timing as well as lower net other and interest expense.

Now on to our segments. Design Automation segment revenue was approximately $2 billion. In addition to strengthen Ansys, the segment saw strong growth in hardware-assisted verification, partially offset by the Optical Solutions Group divestiture. Design Automation adjusted operating margin was 47.3%. Design IP segment revenue was $407 million, down approximately 6% year-over-year and flat sequentially. We continue to expect fiscal year '26 to be a transitional year for the business as our IP road map continues to make steady progress. Design IP adjusted operating margin was 16.2%. Free cash flow was approximately $822 million in Q1, and we ended the quarter with cash and short-term investments of $2.2 billion. Total debt at the end of Q1 was $10 billion. We have repaid the entirety of the $4.3 billion term loan, consistent with our commitment last quarter.

Now to guidance. Our full year targets are: total revenue of $9.56 billion to $9.66 billion. We continue to expect Ansys revenue contribution of $2.9 billion at the midpoint, growing double digits. Total GAAP costs and expenses between $8.46 billion and $8.60 billion; total non-GAAP costs and expenses between $5.69 billion and $5.75 billion, resulting in non-GAAP operating margin of 40.5% at the midpoint; GAAP earnings of $2.21 to $2.62 per share, non-GAAP earnings of $14.38 to $14.46 per share, up $0.06 from prior guidance due to lower net other and interest expense in Q1. We still expect cash flow from operations of approximately $2.2 billion and CapEx of approximately $300 million, resulting in free cash flow of approximately $1.9 billion. With the term loans fully paid off and a strong cash position, our Board of Directors has replenished our existing stock repurchase program with authorization to purchase up to $2 billion of our common stock. Our capital allocation priority will continue to be investing in the business with flexibility to opportunistically repurchase shares while paying down debt.

Now to targets for the second quarter. Total revenue between $2.225 billion and $2.275 billion, total GAAP costs and expenses between $2.02 billion and $2.085 billion, total non-GAAP costs and expenses between $1.38 billion and $1.41 billion. GAAP Earnings of $0.23 to $0.43 per share and non-GAAP earnings of $3.11 to $3.17 per share. Our press release and financial supplement includes additional targets and GAAP to non-GAAP reconciliations.

In conclusion, 2026 is off to a strong start and we're executing to the priorities we've laid out at the beginning of the year. With our broad leadership portfolio, expansive market opportunity and technology trends that play to our strength, we are focused on executing with financial discipline as we solve our customers' biggest engineering challenges from silicon assistants.

With that, I'll turn it over to the operator for questions.

[Operator Instructions] Our first question today will come from Charles Shi from Needham & Company.

So the first one I want to dig a little bit more into the IP segment. Thanks for the commentary muted growth for the year, but sequential improvement from here. For the remainder of the year, but it does look to me that the second half IP revenue should see some pickup. I'm not questioning you that you're not going to deliver that. But I think going back a couple of years, you talk about visibility in some development milestone based IP revenues probably coming from some of the foundry customers, but that part of the business is going away. So wondering what is the confidence on the second half IP business, the pickup? And maybe I can ask a second question after this.

Yes, sure, Charles. The confidence in our IP business is driven by the design starts. As I mentioned in the prepared remarks, for the AI segment, the design start remain very robust. And that's where we engage the customers early and have the opportunity to sell the IP as a portfolio with the various needs that this customer has. And we have an advantage in these situations, given the breadth of the portfolio. So that's one aspect.

The other aspect that has changed over the last number of years is the pace and time in which these tenders are evolving, where historically the standard life used to be 3 to 4 years. Right now, it's about half that time. And the reason for that is the increased need for higher bandwidth, lower power, et cetera, standard. The last point we're seeing and observing is are customers looking for foundry optionality and given the Synopsys portfolio is across multiple foundries with all of that is giving us that confidence.

Now as far as the second half as we have communicated a number of -- a couple of quarters ago, that we have some work to do on some of the schedule on delivering on a few of the titles, and we're on track to deliver to that with an expectation that we'll be able to monetize toward the latter part of the year.

Yes. And I would just add on, Charles, that the availability that Sassine talked about is a little bit more Q4 weighted.

Okay. A little bit Q4 weighted. Maybe a follow-up question. We're also seeing -- I think in the past, you talked about not having the right resources to capture some of the IP opportunity because of -- there was a little bit of focus probably on the foundry side of the customer, but some of the hyperscalers probably needs a little bit more handholding. Wondering if you can give us a little bit of update other than -- I think that you talked about some work will be delivered in the second half of the year. But any sort of update on that front, that would be great.

Yes, Charles, to be clear, we absolutely have the right skills. And what we have communicated, it was a prioritization of some of these skills to deliver on the schedule required for some of these hyperscalers. And again, it's not a question of do we have the right people with the right skill set and understanding, knowing what we want to build. Those are things that we absolutely do have. It was putting the right resources and priority of the resources to deliver on time and schedule for these titles, and that's exactly what we're doing. And I feel great actually about the progress that we're making on our road map and schedule to deliver to these opportunities. .

Gary Mobley from Loop Capital Markets.

Maybe this is a question for Shelagh. But I noticed the RPOs are down modestly on a sequential basis. And it's clear that the fourth quarter of last year was a strong bookings quarter. So maybe if you could speak to the seasonality of the bookings as you see it on both for the balance of this fiscal year and in general, talk about the renewal activity on the EDA side and the simulation software sides of the businesses.

Well, as you know, it's an ebb and flow of building and consuming backlog, we feel great. We are sitting at $11.3 billion of backlog. So we've got a strong understanding of what our customer demands are and what we need to deliver to them. And as you said, just kind of ebbs and flows with renewal timing. So there's nothing there's nothing about backlog that does anything other than give us confidence sitting at $11.3 billion.

Okay. If I could just ask a quick follow-up on the verification and hardware side of the business, how do you see the product cycle of ZeBu and perhaps 200 playing out for the balance of the year in comparison to last year? And where are we at in terms of the product cycle strength?

Yes. So exactly what you pointed out. We have 2 parts of our hardware portfolio. We have ZeBu and HAPS, and we introduced the EP family, which is an emulation prototyping, which is a hybrid that provides our customers the flexibility to achieve the highest performance that is needed for software development as well as the ability to verify the function of the chip. We had a record year last year. And it was following a number of other record years, and we have an expectation for that business to continue on delivering to such expectations given the demand and complexity that our customers are driving that requires both a ZeBu, HAPS, EP system, and we have a number of use cases today that we're leading the market in terms of technology differentiation there.

The next question is Jay Vleeschhouwer, Griffin Securities.

So seeing the first question for you and perhaps somewhat technical. You began your remarks by noting how AI could be variously constructive to your business rather than disruptive. And I'd happy to agree with that. But I'd like to ask about 3 ingredients that you might have to execute upon to make sure that continues to be the case. We hear a lot, for example, about orchestration requirements across genic AI. I think that's probably going to pertinent to EDA as well or engineering software broadly. Secondly, data repository across a broad apps portfolio that you now have. And then finally, traceability, particularly for simulation, but also more broadly. I know it's a little technical for a call like this, but perhaps in so far as those are, I think, critical ingredients, maybe talk about your capabilities there? And then the follow-up to Shelagh.

Yes, Jay, thank you for the question. If you recall, last year at Converge, we put our road map for agent engineers. And in that road map, we mapped out L1 through 5, where L1 think of it as a reinforcement learning applied to every aspect of the technology that we offer in L2, where we have what we call the task agent an L3 into orchestration of these agents and L4 into the planning, et cetera, into a full autonomy of orchestration where the human engineer will be dramatically augmented and the workflow will change on how to design the chip. Now what stitches all of that together is a visibility and continuum of data, exactly the second point that you're mentioning. And then, of course, the traceability, visibility into the accuracy of the verification because at the end of the day, what we do, our agents cannot hallucinate. They have to be 100% accurate as you move to the next phase and the following phase of the workflow.

We have a number of the tasks agents and we have multiple orchestration layer, and we talked about this through some of our partnerships we have with NVIDIA, with Microsoft, et cetera, to leverage some of that orchestration layer and the cognitive layer that they offer. So it's a combination of what we're building and what we're partnering with the ecosystem in order to accelerate our road map on the vision of an agent engineer, which we believe strongly that we have pioneered and we continue on engaging the customers there. But I want to make sure that it's clear as well in order to deliver to that vision, you need the data and you need the verification ability of every step of the flow.

Okay. Shelagh, for you with regard to Ansys, 2 things stand out in the results and outlook. And so the question is really about the forecastability of the Ansys business. It remains clear that their results are still heavily influenced by pronounced 606 effects, which was certainly the case for them before the acquisition. So maybe you could talk about how forecastable the Ansys business is, given that variability in that particular accounting and then also we think about the renewals cohort from 2023, it was heavily reliant upon automotive. That's where they had their growth 3 years ago. So presumably, that's where you're going to have to rely upon the renewals cohort growth for this year as compared to A and B and high tech. So maybe talk about some of the end market assumptions behind your forecast for Ansys for this year. .

Yes, I'll start with the back end of the question, Jay. So as we have the capability in Ansys really to service multiple market segments, that's what gives us a lot of confidence. You know simulation and analysis is still very lightly penetrated in the TAM. So there's ample place ample opportunity not only to grow within customers, but actually grow new customers. So that opportunity set is quite broad for us. And then in terms of how we think about the business, as you know, the December was always very big for them. That happens to have fall into our Q1. They were a fiscal year. Obviously, we're a [ 10 31 ] year. So what you saw in Q1 was the combination of what they would have been their typical year-end. So that's a real stand out in terms of our Q1 results. We anticipate that over time, that probably changes as the sales team realigns with sort of our fiscal year. But nonetheless, what we're seeing is broad opportunity really across all those segments. And as we build the forecast, incorporates what we're seeing in existing customers, what we think the new opportunity is -- and then in terms of the 606, as I talked about last time, as we're bringing Ansys in, we're building combined products where a portion of Ansys will be in what we call SCBU, which will be with we're harmonizing those accounting policies really aligned with how we're supporting the products and how we're giving further updates on the product. So over time, that's a more muted impact. And I would say, really, what you're seeing here is there's just a really broad opportunity in terms of ability to service multiple markets with the leadership product finance.

Jason Celino from KeyBanc Capital Markets is next.

Sassine, I wanted to ask about the park processor business that you're divesting, so I understand portfolio review and you're sharpening your focus in other areas. But presumably, this was a core part of your portfolio before. And should be well positioned for physical AI. If physical AI is such a big opportunity on the come. Maybe it's not a growth driver today, but could be, I guess, why the rationale on the divestiture.

Sure, Jason. The ARC business went through a couple of transformation from the self architecture to the risk 5 ISA architecture. And what we are seeing is many of our customers are developing their own processor IP using, for the most part, our software, EDA software to design and verify using the EDA software, our hardware portfolio, et cetera, to develop their own processor for all kind of embedded applications, which is still a great opportunity for Synopsys. So we will continue on enabling enhancing, leading, supporting our product and our customers for their own development. .

From an IT point of view, we believe when we look at our broad IP business and the portfolio we have, there's a much bigger opportunity and a growth opportunity for the interface IP, and this is where we want to capture this opportunity and put our investments at. And GF will be a great partner to -- as they enable that part of their business on both the interface IT side and the EDA side and their engagement with our joint customers.

Okay. And then just for clarification, kind of on the IP messaging. I assume that because the divestiture hasn't closed yet, the ARC revenues are included in in the sequential improvement that was discussed? Or is that not included?

Jason, that's correct. Until we close the Arc is a part of our financials.

Okay. Any sense on how big it is just so we like are able to anticipate?

No, we haven't provided that.

The next question from Vivek Arya from Bank of America.

This is Liam Pharr on for Vivek. You closed Ansys in July last year. What have you noticed by way of cost or revenue synergies thus far for fiscal '26 has been speaking with customers on joint Synopsys Ansys products?

Yes. Liam, what we communicated was the first half of '26 will be when we delivered the first wave of the joint solutions, and I'm looking really forward to communicating at Converge, which is our conference in a few weeks, the rollout of a number of the joint solutions with clear visibility to which market, which customer, and then, of course, once you release a product, you focus on the customer adoption and monetization. And we are anticipating the monetization of the joint solution to start in FY '27 and with quite a bit of excitement from our customers to solve real problems that they have been looking forward for that integrated solution to come.

And I would just comment that the teams were already trained on cross-selling to existing products. So Synopsys sales team being able to sell Ansys products, Ansys sales team being able to cell Synopsys products. So we're well underway in that and we do have revenue this year. We haven't given specific amounts. Our commit is $400 million in revenue synergies run rate by year 4, obviously, incorporating those joint solution that Sassine talked about. In terms of cost synergies, our commit was $400 million run rate by year 3. We're well underway accelerating that. And as you -- as we've worked through, we're working on accelerating that into year 1 and year 2, which is 2026 in 2020. So we're well on way on those.

And then for a follow-up, I want to go a little deeper on China. I understand it remains challenging. But what are the puts and takes in it being flat or even growing year-over-year this year? And have you seen any change in the competitive landscape against a peer who continues to see a healthy design activity environment there? Any on that would be very helpful.

Yes. Sure, Liam. China for the quarter for Q1 performed in line with expectations. As we mentioned as well in the prepared remarks, the Classic synopsis was down slightly, whereas Ansys portfolio performed fairly well. Now the reason you're seeing that mix per se in the performance is the cumulative impact of the restrictions, both in entity list and technology are truly having an impact on our customer commitment and demand. The reason it impacts Synopsys in a greater way, I want to say, is the mix in our portfolio we have a leadership position in our IP business. That part of the business in China, customers may decide not to go for an external foundry and look at the domestic foundry for an example, and therefore, that will impact the IP business, but it may not impact as much the hardware business or the EDA business. So that's from a macro standpoint, the way we're seeing the landscape in China.

As far as the domestic competitors, yes, we're seeing them because, obviously, if customers cannot use our technology, they're looking for alternatives. And the customers who can use the technology that absolutely still prefer to use our technology versus domestic.

2

The next question is Kelsey Chia, Citi.

So my question is on IP. So I understand that it's not so as a leader in interconnect IP with PC-24 service, but the company is also late in terms of IP delivery. And there are that Synopsis may miss customer design starts or customers may shift away from using the IP that Synopsys has developed.

Kelsey, the it depends. And let me explain why it depends. What we sell to is the customer schedule. Customers engagement starts with aligning what we have to when do they need the IP and their tape-out. So a number of the ones that you mentioned, the PCIe or the 224, I'll expand it into an HPM LPDDR, UC which are all titles that customer need in order to design a high-end HPC chip. And for a number of those customers, we are engaged, we're selling that whole portfolio based on aligning the schedule. The comment I made earlier where we do have the expertise, we do have the capacity is the prioritization for specific customers to deliver. And we're putting a lot of focus on that, and that's why the point Shelagh made earlier that our confidence in the second half weighting is coming through the road map alignment and by when do we deliver on these titles.

Got it. And a short follow-up. So IP operating margins are be priced today. Is there -- have we used a role of SK to think about the operating margins at a normalized level? And also, you did talk about actually moving to our royalty business model. So is there a framework to think about a normalized operating margins for IP?

Let me take the operating margin, and I'll have Sassine comment on evolving the business model. So as we've talked about IP growth this year is muted we're still investing to build out the titles that Sassine was talking through. So we've got the engineering team working very diligently, making lots of progress on the titles. But with muted growth, we get muted operating margin. So for this year, we're going to see more muted operating margin over time, though, once we get to the -- back to having the titles on time, my expectation is that's a very good business. So the operating margin will always be below the corporate average because it's more people-intensive but that's my expectation. That's how we've run that business over time. But you will see muted compressed operating margin this year, just driven by the muted revenue, and we're not changing our investment profile there because we're still building out those titles.

Yes. In terms of the business model, the -- I'll start with the market. The great news is there's such a high demand for customization as well as acceleration of delivering on the IP titles, in particular, for hyperscalers because they don't have their own IT team. They are counting on us to be able to deliver on time and what we call one generation ahead for various of the titles I just mentioned earlier. Therefore, it's an inflection point. It's a great opportunity to focus on the quality of the deals and capturing the right monetization for that value, with in active conversations with a number of these partners, and I do expect that we will close a number of these conversations will move into an actual business in FY '26. Of course, you won't see it in terms of that upside until we deliver and the customer tape out and start delivering product for it. But we're very excited about this opportunity to improve the monetization. .

Your next question is from Lee Simpson, Morgan Stanley.

Great. Maybe just 2 quick ones from me actually. We did hear from a peer last week that the monetization perhaps on a Gentek play would come on a value-based basis, perhaps even on a token-based basis. I wonder if you guys had looked at doing things on that. Similar format and whether or not this business could -- and I'm talking about agent engineer here, whether or not that could be margin accretive from day 1? And maybe as a follow-on, if we look at Ansys, clearly a market leader and its product range, but quite broad-based and its customer range. Does that maybe carry some extra risk because value isn't even across all those customers. There's some areas where there's clearly higher value, for instance, to the ICs, the emulation thereof. And so could that maybe perhaps slow some of the growth through this year and into next or Ansys or at least have some risk of it?

Lee. On the Gentek, as we communicated about a year ago when we introduced the agent engineer, is that the workflow will change. The moment the workflow will change, it's an opportunity for us to adjust the monetization based on value. So yes, what you commented on will value base be in consideration, Absolutely. That's what we've been communicating for about a year now that the workflow will change and there will be a monetization adjustment. And the customers, by the way, they are very receptive for that conversation because they understand that they have to change as the workflow changes and how will that value equation from a time-based license to a different type of license as we're accelerating their ability to deal with complexity and schedule.

Now on Ansys, we see Ansys as a force multiplier for our business. As Shelagh mentioned, when you look at the various markets, that are doing engineering R&D, the penetration of sophisticated simulation analysis, CAD environment, et cetera, has a significant opportunity, very different than semiconductor that the Moore's Law pushed and accelerated adoption of EDA. Now with physical AI, if you are an industrial or automotive or robotics, you cannot build those products without investing more in R&D and therefore, investing more in system level design, simulation and analysis. So as the results speak to themselves for Q1, this is not a one-time phenomena. We see that opportunity for the long term, as I mentioned, as a force multiplier and an expansion in customer base for Synopsys that we're very excited about.

Next, we'll go to Siti Panigrahi from Mizuho. .

Can you hear me?

Yes, we do. .

I don't know this question may answer a question is about your NVIDIA partnership that you announced recently. There is a big investment from NVIDIA. I'm wondering how that partnership coming along? And how should we see about the product priorities evolved? And how you think about the monetization there?

Yes. Siti, the way I explain this partnership, at least internally. This is not a press release partnership. It's a deep commitment from both companies that we both saw a market opportunity that we want to accelerate and capture. And it comes in 2 forms. The first form is a road map we communicated on bringing number of our products, EDA as well as the legacy Ansys products into GPU acceleration and delivering the multiples of acceleration that is -- that we set as a target and a goal between the 2 companies. So we have a joint R&D working on these products with an expectation to deliver a number of them in '26 and that will come with an upside in a business model, meaning if you're using a product A from Synopsis suing on a CPU. That will continue that road map will continue and will have a parallel product of that product running on a GPU. And if it's delivering 15, 20x, then there's an uplift for that value we're delivering to the customer. That's 1 layer. The second layer is Omniverse, the ability to create a digital twin for the physical AI opportunity. Physical AI is not possible. by having an old method physical prototype, you need to create a digital twin, a digital twin is useless without an accurate simulation and analysis. And that's where we come in. That's where the Ansys portfolio comes in and we're we want to lead the opportunity to monetize on both the GPU acceleration as well as the digital twin opportunity for physical .

The next question will come from Gianmarco Conti, Deutsche Bank.

So maybe I just want to go back on agentic. Could you perhaps give us some color on where you currently sit with customers using it for both front end versus back end? And whether you have a sort of like an idea of customer penetration into the next 12 months? And how are customers using it right now? And will they require higher competition or needs as their designs are scaling faster with more agents. And I'm just kind of curious as to how the delivery method being addressed to these customers as the part, for example.

Yes. I'll talk more about it, and Shankar will talk more about it at Converge. But at the high level, what we have right now is number of tasks, agents. For example, I mentioned in my prepared remarks, some value we're seeing with the formal adviser. That's an area where the test coverage has always been a very time and compute consuming task for our customers. This is a great opportunity on how to leverage both an agent to be able to look at a specific task and series of agents to orchestrate and accelerate the -- both the coverage and the whole verification opportunities. So your question about front end and the back end, we're working absolutely on both where the early opportunity that we're seeing, and we're tackling it because of the bottleneck that our customers, they do see in terms of time and number of engineers they put is in the front-end area. But we have a road map on both. So this is something stay tuned. We'll communicate more at Converge, but we're seeing great progress based on the number of customers we're engaged with early with early engagements.

Got it. Shelagh, maybe just one last one for me would be what's driving the lowest GAAP EPS guide despite gap expenses being lower?

So I think real delta this year between GAAP and non-GAAP is if you look at -- it's really the amortization schedule, and there's more detail in our quarterly filing on that. So we've got the restructuring, which is onetime only. It's '26 and '27, but there will be an amortization schedule that will be rolling through over the next several years.

Next up is Joshua Tilton, Wolfe Research. .

Congrats on this, I'll start for the year. I have 2. My first 1 is more of a longer-term question. And I guess the question is, Citi, I think the words you used were 2026 is the year that you begin to deliver on the technology promise of Synopsys plus Ansys. And what I'm trying to understand is and I'm assuming you will. But when you guys do deliver on this technology promise in 2026, what does it mean for the direction of growth for your business in '27 and beyond? I think a lot of investors see the growth that Cadence is putting up and they're kind of excited for your organic growth sort of trend in that direction. So any help or any color would be greatly appreciated.

Yes. Sure, Josh. On -- as far as the long-term growth view, it has not changed. On EDA double digits on IP mid-teens as well as on the simulation and analysis is a double-digit growth. So that puts the company as a whole in a double-digit growth opportunity driven by the demand and the leadership we have in our portfolio. When I say that 2026 is the year where we begin delivering on technology and the value promises. There are, today, problems are not being solved with the current offering that the industry is providing the customers.

And when we talk about the joint solutions, how to bring in physics analysis into the design phase when you're designing a multi-die system. A lot of the challenges our customers are dealing with is they design they go to sign off, they discover an issue, say, a thermal or a structure issue then they have to iterate and iterate in order to solve. So that takes time and risk. And this is what we're so excited about with the joint solution, given what Ansys has is the leadership sign-off for physics and what Synopsys has is the leadership position in the design platform and those were the joint solution come together that our customers are anxiously waiting to see innovation and bringing these 2 platforms together. So that's where we're seeing the opportunity of growth.

Now as we compare to the market or our closest peer, our commitment is on what I just mentioned in terms of double-digit growth. In IP, in particular, we have communicated and we repeated that it's a transitional year for us for '26, but the market opportunity is there. We have the scale, we have the skills and we have no doubt that we will deliver to our long-term view for IP.

Makes sense. Maybe just a quick follow-up for Shelagh. More of a clarification question. Did I hear correctly that relative to your guys' expectation that it was Ansys that drove most of the outperformance of the revenue guide? And if that is the case, when we think about the potential for upside throughout the rest of the year, are we planning for that upside coming from the Ansys business and more of an in-line year for the organic business? How do I think about that? So we saw significant strength in Q1 in Ansys. So as reflected in what we shared, the $866 million for Ansys. So the strength we saw was really across the industries that Ansys sells into. And then for the full year, obviously, we don't guide by segment, but we're looking for strong performance across all the lines.

The next is Joe Vruwink, Baird.

I wanted to ask about EDA software specifically within design automation. If hardware was a big contributor to the strength for the overall segment, I'm assuming the software piece is still growing in the single digits. Maybe can you walk through some of the biggest items in your mind that start to lift the growth profile in the EDA software business higher? And are you seeing any evidence of that yet in bookings or renewal opportunities that are on the horizon?

Joe, on the EDA software, given this is a ratable fairly predictable type of business. We know when the renewals are coming up. We engage with customers early to deploy new technology. It depends on the customer. When I talk about the tail of 2 markets, the first tail that are serving AI build-out. Those are the customers that they are racing to deploy the synopsis. AI, racing to deploy the 3DIC Compiler, Fusion compiler, PrimeTime, VCS, et cetera. We have, as you know, a leadership position in the EDA software, and we continue on collaborating, engaging early and finding an opportunity to upsell during or between renewal cycles.

On the second tail of customers where the R&D investment and the push for acceleration has not been as strong as the first tail. Typically, our renewals are timed with the monetization is timed with the renewal exploration. But net-net, the EDA software for us, we are excited about all the opportunities the Classic Synopsis has been building. The next opportunity, of course, is the joint solution that will leverage the Ansys portfolio to create the new product and a new opportunity to monetize.

And everyone, that does conclude our question-and-answer session. I would like to hand the conference back to Sassine Ghazi for any additional or closing remarks.

Thank you. It's such an exciting time to execute as one company and Ansys now part of Synopsys. With that, we have extended our technology leadership into simulation and analysis and we expanded our customer base into new market opportunities. The other point is on AI. AI is absolutely a trend that is fueling system level and semiconductor R&D investment. And our AI products are capable and are mission-critical for our customers' success. We are focused on executing with financial discipline as we solve our customers' biggest engineering challenges from silicon to systems. Big thank you to the global Synopsys team for a strong start to 2026, and thank you all for joining us today.

Once again, everyone, that does conclude today's conference. We would like to thank you all for your participation. You may now disconnect.

Hello. Good morning, good afternoon. Welcome to the 28th Annual Needham Growth Conference. With me here right now is Shelagh Glaser, Chief Financial Officer of Synopsys. Shelagh, thank you for being with us today.

Charles, great to be here with you.

Well, before we start, allow me to read the safe harbor statement from Synopsys. Today's discussion may contain forward-looking statements related to Synopsys' current outlook, expectations and beliefs, which are subject to certain risks and uncertainties that could cause actual results to differ. Please refer to Synopsys' most recent SEC filings for a discussion of risk factors that may materially affect those statements.

All right. Now let's get started. Shelagh, I would like to address this question off the top of investors' minds immediately. So last year, you guys closed the [indiscernible] acquisition. I think it's an achievement, maybe still a little bit underappreciated given the very tough geopolitical backdrop. But also last year, you guys had to cut outlook around the fiscal Q3 quite meaningfully. And we all knew that there was -- also was a little bit of a miscommunication issues around that particular print around [indiscernible], et cetera.

So I'm wondering -- if you can take the opportunity today and maybe recap from a fresh perspective today, what exactly happened to last year's business that has led to that outlook cut and as we look at this year and beyond?

Great. Thanks for the question, Charles. So really, what happened in our fiscal Q3 is in the IP business, which is a significant business for us, we saw 3 headwinds that we are navigating through. So the first headwind is really China. And what happened in our fiscal Q3 in China was there had been restriction on the EDA technology. And so you say, well, the IP is not affected by that. But it really caused a significant customer disruption because it caused great uncertainty in the customer base. And as they were thinking about their road maps, trying to understand and navigate an uncertain environment and navigate what could impact their business, the IP decisions got delayed or contracts got downsized because of that, just because there was uncertainty about what environment they were operating in, they took a step back to rethink their road maps and IP is an upfront revenue for us. So that's a headwind inside the quarter, and that was a headwind in Q4. The second one is some challenges in a foundry customer. And you can think about we support all foundry customers universally. You can think about our IP as being critical for those foundry customers to be able to gain customers into their foundry.

And so one of our foundry customers actually had some headwinds in terms of their ability to get customers. And so that's an impact to us. We've got resources dedicated to that. We have expectations on that. And so that's a headwind for us in terms of revenue. Related to item #2, we had areas where on HPC titles in particular, we didn't have enough resources. And so what we've done is we shifted resources to where we see the demand, which is the HPC titles, but that doesn't happen instantaneously that then the HPC titles are available. So what we've done as a consequence of all this is as we put the forecast together for 2026 and how we thought about guiding 2026, is really ingesting all that and ensuring we're derisking our 2026 guide.

In light of that, we think the China headwinds persist. We do not anticipate a different business environment in China in 2026 than we had in 2025. So we think some of that customer disruption and uncertainty, that's the same environment. In terms of the foundry customer, we assume and the way we built our forecast, we don't assume that foundry customer is getting additional customers. Our forecast doesn't assume that. And then in terms of the reapplication of resources, our -- we've already done that. So that work is already completely ensued, but some of those titles won't be available until second half of the year. So that informs how we put our guide together.

In terms of Ansys, we got very clear feedback, which was very welcome to make sure that we are fully visible and fully transparent. So what we have done is, as a consequence of that, we've given full visibility into Ansys even as a part of the guide, we gave full visibility into Ansys. So we took that feedback very seriously, and we've built that into how we're moving forward and how we're communicating moving forward.

Thanks, Shelagh. That was a great recap and a great rundown of the assumptions baked into this year's outlook guidance. So I would like to explore like the business segments one by one, and let's start with Ansys. So yes, as you just mentioned, right, around your fiscal Q3 earnings last year, people were a little bit worried about Ansys because a little bit lack of visibility into how that segment was performing, given the segmentation decisions you had at the time, but then you kind of corrected that in Q4, given us the full visibility.

And it does look like Ansys has been performing very well. And I would argue maybe -- I mean, on a short-term basis, of course, this is performing better than your EDA and IP segments. And so what's driving the Ansys outperformance right now? And what are the factors you think should hopefully sustain that strong performance into 2026?

Yes. So Ansys has been performing very strongly in '25, and we anticipate '26 is another strong growth year for Ansys as we've given the outlook. And it's really Ansys and it's the reason that drove us to do the acquisition of Ansys, they have the leading portfolio in simulation and analysis. Their product portfolio is really unmatched. And really, what we're seeing is the broad applicability of their tools. You can think of really almost any R&D team can benefit from the simulation and analysis tools inside Ansys.

They have leading thermal mechanical, fluid dynamics. And you can think about almost any R&D project will benefit from the ability instead of building a physical prototype to do simulation and analysis where you can really understand whether what you're designing is actually going to be what you end up getting in manufacturing. So we're just seeing broad strength across that portfolio because, again, it's the leading tools in the industry. And we're seeing a lot -- I mean, simulation and analysis is still very lightly penetrated. If you think about the tools that we use on the digital design side, nobody would make a leading-edge semiconductor without our design tools. But you can think of sort of the rest of the R&D world, simulation and analysis is still only a few percent of those R&D dollars. So tremendous opportunity and the leading portfolio in the industry.

Yes. That's great insight. Yes, the EDA, I would argue it's a good chunk, double digit of the R&D budget, right? And yes, it's great to hear. That's a good amount of upside. So now, Sheila, you have managed the Ansys portfolio as the CFO of Synopsys for roughly 7 months, I guess. In terms of the post-close integration targets like deleveraging, like cost synergies and maybe revenue synergies a little bit down the road. Where are you relative to the targets you set when Synopsys first announced the deal like that was 2 years ago? And any upside surprises or downside, if you will?

Yes. So we -- as you said, we closed the transaction in July of last year. So we're well underway with our integration. It's been very seamless. The teams are working super collaboratively together. So it's been actually a great joy to have to see those teams work together and see the excitement between the teams, be able to just work hand in hand. So on cost synergies, we're accelerating the cost synergies. So as we announced a significant operating margin improvement year-over-year, we're taking -- we announced a restructuring. So we're taking the opportunity to make sure that we are capturing those synergies as we're kind of now one joint team. And so we are well underway on those cost synergies.

In terms of deleveraging, we've already made significant progress in the term loans. As I shared in the earnings, we expect in the first half of '26 to really complete those term loans. So we're very dedicated to the deleveraging. We're moving very rapidly for that.

Obviously, the bonds are -- don't start until '27, but we're making significant progress on those metrics. And then as you said, revenue synergies are really the $400 million run rate by year 4. And frankly, that's just because we're building out that joint road map. We'll have their first solutions in '26 of the joint road map, but that's ongoing. We'll build that road map out. The teams are already working on cross-selling. We've cross-trained the various teams so they can sell the various products. So we're actively working on that. But those joint products, those will build over time. So that's why that synergy on the revenue side is a little bit longer.

Great. Should we be expecting some announcement around the joint products around -- it's not called the Synopsys Converge event.

We'll certainly talk in more detail at our SNUG Conference, which is our Synopsys User Group Conference. We'll certainly talk in more detail.

Great. Looking forward to that. So let's talk about IP. This is the area despite all the challenges last year, you just mentioned, this is an area where Synopsys is the industry leader, I mean, probably indisputable at all, right? You are the leader in IP, especially at least around everything around the processors, right? And the long-term strategy, right, of maybe moving to subsystems or some of the HPC titles you just mentioned about, there's a lot in there. I'm wondering if you kind of walk us through what's the longer-term strategy, how you think about growing the IP, I mean, despite all the challenges you faced last year and how to like play to your strength a little bit even stronger in the coming years?

Sure. And as you said, we are the leader in interface and essential IP and processor, obviously, ARM is the leader in processor IP. And that is a critical area because all of that -- all of those GPUs, CPUs, whatever the engine is, they need all that interface IP. They need to be able to talk to other parts of the chip to other chips to the outside world. And so the importance of it is significant. The pace at which basically the standards are moving is a pace we've not seen before. It's the pace at which the kind of the AI cohort is driving the standards is very rapid because, of course, you need these IPs to keep pace with how fast the engines are moving because they can slow down the capability of the engine if they're not moving at that.

So that's a great opportunity. Basically, these standards moving in a much more rapid pace. The other opportunity that we see there is in the data center AI cohort, we see that, that group of customers not only are buying merchant silicon, they're also partnering with some of the ASIC capability companies who we also partner with to provide IP and they're also building their own designs. So we have the opportunity, obviously, on the first one, we're already working with those merchant silicon companies, but on the second 2 to actually service them through that.

And on the third one, where they're building their own chips, we're seeing them actually want custom -- so yes, it's a standard, but they want something tuned exactly for the workload because if it's tuned for the workload, then that helps them have a much more optimized solution that helps them have a much better product or capability. And so that's an opportunity.

And with those customers that are in that subsegment, we're also having conversations with them on evolving the business model. And so how do we think about evolving the business model with them over time. So that's an opportunity. And then as we move further out in time, some of the opportunities that we have as more customers sort of move into that smart space, the customers that aren't the fast-moving IP customers, they're certainly going to want to inherit some of the learnings on that. We've talked about sort of the tale of 2 markets.

We don't see automotive and industrial at this point moving at the same pace of AI, but we certainly see areas where they're going to want more capabilities, more IP capabilities as they build more sophisticated chips over time. And so we think there's tremendous demand, tremendous opportunity and the pace at which everything is moving really means that the kind of the constant fresh IP is a big opportunity for us.

Great. Great. So maybe this is a very timely I mean, discussion. the sale of the ARC process IP you guys announced a couple of days ago. So what's the rationale behind that transaction, at least from Synopsys perspective? As I believe you guys have owned that portfolio for since I think probably 2010, that's the day I found. So more than 15 years only that why selling it now?

It's really about us prioritizing and really making sure we're focusing on the areas where we -- our strategy is to lead, which is the interface IP and essential IP. And so when we looked at that and we looked at the opportunity, Charles, that you and I just talked about, that's a tremendous opportunity for us. So the processor IP, it was not the priority for us. It's obviously a great match with Global and what they're driving their strategy.

So it's a great asset. So it's essentially a priority for them. It's -- for us, we really want to be the leader and really be very focused on interface IP and essential IP and be able to service our customers. And so for us, that's our top priority. And so as a part of that, moving that asset to a place where it's a better fit was a really good outcome.

Great. I think you touched upon the monetization business model for IP. I mean, if I understand you guys correctly, it used to be -- I mean, it has been mostly driven by development and usage. That's how you charge for the IPs as of today. But royalty looks like you guys are looking at that as a third avenue, right, of IP monetization. But there were not many very successful royalty-based IP business model out there. Maybe Arm is one, but how realistic do you think a Synopsys can maybe migrate to a royalty-based IP business model given what you see today?

Yes. And just to put it in context, we're talking about the customers that are in the data center, AI, where they're pursuing their own road map. So they -- again, they kind of have 3 models. They're doing merchant chips, they're doing ASIC chips and then they're pursuing their own road map. So it's in that segment, that small segment of customers, where the conversation is for IP, we have basically an NRE and then we have a use fee.

What we're talking with those customers who are asking us to dedicate resources because, again, this is a big unlock for their road map and the drumbeat that they want to drive their road map on to make sure that they've always got these IP blocks ready to go. We're talking about another element of monetization with them because that's obviously higher value for them to be able to have these capabilities at the ready for them to accelerate their road map.

How do we think about adding additional value for value monetization model. And then we're having a conversation about our royalty base. That obviously has -- is a tail. The NRE and the use fee are upfront, a royalty is over time. And again, it's in that subsegment of customers that we're having that. And so those conversations are ensuing in those discussions. And so we'll obviously evolve that conversation and evolve how that flows into the business model. But it's not moving from -- the whole business model is not moving to a royalty business model.

It's in those cases. And I think if you think about the pace and change of the industry and the pace and change of those customers, the business model does need to evolve. Their business model has obviously evolved quite significantly. And so us in support of them having that successful outcome, that needs to change.

Makes sense. So going to be -- it sounds like going to be pretty selectively, maybe start somewhere in those specific areas where this model may fit better. It sounds like that's the case.

Correct. Yes. So it's very focused, yes.

Got it. Got it. Okay. So Shelagh, let's talk about EDA. So I think last year was exactly at this conference, right? I think you and I had a similar fireside chat, and you basically talked about semiconductor market as a tale of 2 markets, between AI, AI has and AI havenots. And you basically -- I think you were -- you alluded to that the EDA growth maybe could be still a little bit muted. That was last year's comment, given that dynamic between AI and non-AI. A where we stand today, do you still see a tale of 2 markets?

And what do you think could drive EDA growth kind of back to low double digit. That's still your long-term target, right, for EDA. But the last year, last couple of years, EDA growth, as we can see from your numbers, your peers' numbers, especially around the custom digital, it hasn't been in the double-digit range. So might you give us some thoughts, what needs to happen for that part of the portfolio to reaccelerate again?

Yes. And we do still see the tale of 2 markets. So that persists. So we see the pace at which the AI kind of HPC crowd is moving -- cohort is moving is much more rapid. And then we still do see that consumer index or industrial and even automotive is still moving at a different pace. So over time, that will change. And then the monetization opportunities inside EDA really are bringing this Ansys portfolio together. That's why we -- one of the motivations for bringing those leading Ansys tools in that we build these joint solutions. So that's certainly a part of it.

And the other one is as we move portfolio from CPU to GPU, that's another opportunity for monetization. And the other one that we talked about, which is much longer term is how we move from the current environment, Sassine calls it reengineering engineering into a more agentic environment and how we move from just having AI as a part of the tool into having an agent as a part of the capability that could design some part of the chip or could run the test or could do something more than just kind of speed things up, actually change the design flow and allow customers to have a much more rapid ability to go from like initial architecture all the way to chip.

Great. Great. So generative AI, that's one potential upside. And the other one, maybe joint development. And the third, I heard you talk about accelerated compute for EDA, right, moving -- migrating to GPUs, 3 opportunities, maybe you can better monetize the EDA products you currently have. It does resonate with us. We do think the EDA is a little bit underappreciated the value you guys provide to the whole industry, you're very enabling. But allow me to double-click on that joint product between the EDA and Ansys portfolio. how that contributes to better monetization.

So we've heard about this argument for many years from you guys, from your peers and that integrating the different EDA tools to put that into one design flow, the full flow supposedly should drive better pricing, but we maybe it's happening, but hardly from outsider perspective, we can see evidence that it's helping with the pricing. So why this time is different, like the joint product between the EDA portfolio and Ansys portfolio, why this time it can help with the pricing.

And certainly, we develop tools in such a way that customers can still continue to buy things independently. So one of the expectations in our industry is everybody has a different design environment. So customers want to tune the design environment. So the portfolio will still be able to be purchased. However, customers want to purchase. But if you want to bring those 2 design environments, so we bring the thermal mechanical environment together with the digital design environment, we're actually solving bigger problems for customers. So if you think about when a customer has a design.

They've got the specs that they want the design to perform to. And then they've got the expectation on what yield and what outputs are. A lot of this is managed in 2 different environments from the design standpoint. So we understand what the chip performance should be, what the power performance area, PPA typically is called what the PPA is for the digital design. And then we understand from the thermal mechanical like what do we want the yields on this chip to be? What do we want the performance, what do we want the yields because of 2 different environments right now.

And so if you want to bring those 2 environments together and you could find out much earlier in the design cycle that there's a yield problem or if you could configure the chips, again, in a multi-die design, you can configure the chips in a different order of operations, of which chip is 1, 2 and 3, and you're solving yield problems, which are really business problems for customers because if you have a yield problem, you have a cost problem, you have a margin problem, you have a ramp problem. So we want to solve big, hard problems for customers, and we want to solve them much earlier in the design cycle.

That lowers cost for customers, increases confidence, improves margin for customers over time and save their resources because their resources aren't working on instead of having a bad tapeout, now we got to go back. We got to make another tape-out, and we got to chew up 6 months of R&D of precious R&D people. I'm in search of solving bigger problems for customers because those customers are trying to make design cycles in 12 months. So if you want to make a design cycle in 12 months, you have to find the problems early, solve them early in the R&D. So that's we're in search of solving that much bigger problem for the customer, much higher value problem set, therefore, much higher value for what we deliver.

And again, people can still purchase things separately. If that's not a high-value problem that somebody has, they would still be welcome. But in these joint solutions, that's what we're after, solving those higher-value problems. And then it's up to us, to your point, to make sure that we're fully capturing a portion of that higher value problem that we're solving.

Great. Great. Well, definitely looking forward to the magic Synopsys is going to bring to the market by using the leading EDA and the leading simulation analysis portfolios together. So Sheila, I mean, for the remainder of the time, I do want to touch upon China. At the beginning, you did mention about you are assuming it's the same kind of environment in China. Nothing really has changed to the upside or downside versus last year.

But yes, I get it, you're not assuming it's going to be a tailwind, but it sounds like it won't be a headwind either. But what could happen? What needs to happen for the overall China business to get better this year?

Yes. So I think kind of our forecast doesn't depend on something better happening in China. To your question, certainly, there has been a lot of uncertainty in the customer base just because there's a lot of tension and therefore, uncertainty in the customer base. And I think to the extent that there can be more clarity, that helps the customer base in decision-making. And when customers are uncertain, they hesitate, they do smaller deals. They may be sometimes might take a chip off the road map because they're not sure -- not that they can't design the chip, but they're not sure will they be able to manufacture that chip? Will they be limited into their use case for the chip. And so to the extent that there could be more clarity, I think that helps customers. And then that helps them be able to make better decisions.

We don't, again, anticipate that the environment will be different. We're certainly still investing in China. We've got a great team in China. We have great customer relationships. So we're not in any way stepping away from China, but we're just trying to be very balanced in how we think about that in our forecast.

Great. And maybe before we open up for Q&A, this is one last question, Sheila, for you. And I'm sure you've been speaking to a lot of investors, probably especially after the fiscal Q3 earnings. And what do you think are some of your messages you feel like maybe still a little bit underappreciated by the investment community as of today?

So I think I would come back to some of the conversation we had. We have the leading portfolio in digital design. We have the leading interface IP portfolio in terms of interface, in terms of essential IP. We're focusing even more on that as we talked about, we're disinvesting even in assets so we can really focus on that. And with Ansys, we have the leading portfolio in simulation and analysis. So the strength of the Synopsys plus Ansys portfolio is really unmatched in the industry. And we're operating in a time where silicon is the heart of everything.

So the customer that we're servicing is really moving -- everything is becoming smart. Everything in the industry is becoming smart. And then obviously, we're seeing AI and physical AI move at a pace that's quite unprecedented. And we're essential essentially for those designs to happen.

Great. Thanks, Shelagh. Let's open up for Q&A. If you are logged into the Needham conference portal, you will see a Q&A box on the user interface and feel free to type your questions I'll ask on your behalf.

Let's give it a minute and see if there are any questions. All right. How about let's just leave it there.

Charles, thanks for the time. Really appreciate it.

Yes. Thank you very much, Shelagh and the Synopsys team. I appreciate you being here, and I hope everyone enjoyed the rest of our Needham conference. Thank you.

Thank you.

Ladies and gentlemen, welcome to the Synopsys Earnings Conference Call for the Fourth Quarter and Fiscal Year 2025. [Operator Instructions] As a reminder, today's call is being recorded.

At this time, I would like to turn the conference over to Tushar Jain, Head of Investor Relations. Please go ahead.

Good afternoon, everyone. With us today are Sassine Ghazi, President and CEO of Synopsys; and Shelagh Glaser, CFO. Before we begin, I'd like to remind everyone that during the course of this conference call, Synopsys will discuss forecasts, targets and other forward-looking statements regarding the company and its financial results. While these statements represent our best current judgment about future results and performance as of today, our actual results are subject to many risks and uncertainties that could cause actual results to differ materially from what we expect.

In addition to any risks that we highlight during this call, important factors that may affect our future results are described in our most recent SEC reports and today's earnings press release. As shown in today's financial statements, all of Ansys revenue appears under the Ansys product group, including the Ansys semiconductor products.

In addition, we will refer to certain non-GAAP financial measures during the discussion. Reconciliations to their most directly comparable GAAP financial measures and supplemental financial information can be found in the earnings press release, financial supplement and 8-K that we released earlier today. All of these items plus the most recent investor presentation are available on our website at www.synopsys.com. In addition, the prepared remarks will be posted on our website at the conclusion of the call.

With that, I'll turn the call over to Sassine Ghazi.

Good afternoon. In 2025, we redefined Synopsys. With Ansys, Synopsys has transformed from an EDA leader to the leader in engineering solutions from silicon to systems. We achieved a record annual revenue of $7.05 billion and exited FY '25 with more than $11 billion in backlog. In Q4, we made strong progress executing the actions we identified to accelerate our strategy and drive long-term growth. More specifically, Ansys integration is well underway following completion of the planned divestitures of the Optical Solutions and PowerArtist businesses.

We've also initiated restructuring actions to drive efficiency and accelerate our committed synergies. And recently, we welcomed industry veteran, Mike Ellow, as our new Chief Revenue Officer. Fourth quarter revenue was in line with our guidance and EPS came in slightly ahead of guidance. Looking ahead to FY '26, we're guiding revenue of $9.61 billion at the midpoint, which factors the addition of Ansys, the completed divestitures and continued pragmatism around China.

Zooming out, we are operating amidst a multitrillion dollar AI infrastructure build-out, which is driving robust semiconductor demand and design starts for both specialized and general-purpose compute. We're also seeing stronger semiconductor demand in mobile and automotive while markets like industrial and China broadly remain subdued. AI will revolutionize every industry, demanding more compute performance while compounding engineering complexity. AI is driving chips to the atomic level while scaling from factory to edge to intelligent devices everywhere. As AI evolves from large language models to world models, engineering AI's future is not just a software challenge, it's a physics challenge. AI makes it both possible and imperative that we reengineer how engineering is done. Building complex AI-powered systems with the right performance, scale and efficiency requires new tools with multi-domain integration and new workflows to enable tight software and hardware codesign. That's why we're so excited about the combination of Synopsys and Ansys.

Ansys diversified our revenue, expanded our customer base and supercharged our opportunity. Together, we can bridge digital and physical design to help engineering teams across industries deliver better products faster and at lower cost. Our recently announced strategic partnership with NVIDIA further positions us to revolutionize design and engineering with AI and accelerated computing.

Now more than ever, Synopsys is mission-critical to technology innovation. I'll briefly share some Q4 business highlights, and then Shelagh will provide the financial details. First, design automation. In Q4, we saw continued strong demand in hardware-assisted verification, driven by the increasing engineering complexity of AI and high-performance computing. Our HAV business ended a record year with 12 competitive wins in the fourth quarter.

We're also seeing continued demand for virtual prototyping among automotive and high-performance compute customers looking to accelerate their software development. Our leadership on advanced node, multi-die and AI design drove steady demand and growth in the fourth quarter. Last week's AWS Graviton5 launch is a great example. For years, we've collaborated with AWS to enable their custom silicon development and Synopsys tools, including VCS, PrimeTime, Fusion Compiler and IC Validator were critical to the design of this new custom chip with impressive gen-on-gen performance gains.

Importantly, Synopsys continues to pioneer AI-driven chip design. Nearly 5,000 active users among our Tier 1 semi customers are applying Synopsys.ai's assistive and creative capabilities to increase their engineering productivity. We also continue to advance AgentEngineer technology with partners like NVIDIA and Microsoft. Agentic AI capabilities promise to transform engineering workflows and unlock new business models.

The Ansys business continues to demonstrate robust growth across key industries, including industrial, where customers are using simulation to virtualize and optimize production, saving time and money. At Microsoft Ignite, we partnered with Microsoft, NVIDIA and Krones, a leader in packaging and bottling, to show what's possible. Using Ansys' accelerated physics solvers, NVIDIA Omniverse and Microsoft Azure, Krones built a digital twin of its bottle filling line to simulate and optimize operations in real time. A powerful example of how open ecosystems and cross-industry collaboration are redefining industrial innovation.

Turning to Design IP, which performed in line with our adjusted expectations. As interconnect standards evolve at an unprecedented pace, customers count on Synopsys' one-generation-ahead approach. We saw strong momentum in the quarter for PCIe 224 gig and UCIe IP. Notably, we secured 13 PCIe 7.0 design wins during FY '25 and established first-to-market position with our silicon-proven 224 gig IP and the new standard UALink. We also had 10 competitive wins in FY '25 for LPDDR6 and MRDIMM2 memory IP, which address 2 critical challenges in AI hardware, data throughput and power efficiency, while also improving reliability and security.

As stated last quarter, 2026 is a transitional year for the IP business, and we expect growth to be muted. However, given our leadership position in essential interconnect and foundation IP, our healthy sales pipeline and a renewed focus on the highest value opportunities, we are confident in our long-term mid-teens growth target.

To sum it up, we continue to transform and drive our strategy forward with a focus on technology leadership, operational excellence and financial discipline. Our priorities for FY '26 include advancing our technology leadership by continuing to pioneer the use of AI for engineering workloads and delivering our first Synopsys-Ansys joint solutions in the first half of 2026 and efficiently scaling to accelerate our strategy through disciplined cost and portfolio management, resulting in sustainable growth and margin expansion.

I want to thank our global team for their commitment and adaptability navigating an unprecedented year of transformation. Together, we've built the foundation for our future success. I'm also grateful to our shareholders, partners and customers for your continued support, and I look forward to seeing many of you at CES in January.

Now over to Shelagh.

Thank you. As Sassine said, 2025 was a transformational year, highlighted by the close of the Ansys acquisition, record revenue and strong backlog. Backlog came in at $11.4 billion, up from $10.1 billion last quarter, driven by strength in bookings across the business. We are acutely focusing on executing with financial discipline as we head into fiscal year 2026. We are well into delivering on our plan to improve efficiency with the previously announced workforce reductions. These decisions are never easy, and I'm thankful to the Synopsys team as we execute these actions and accelerate realizing our cost synergy commitment.

Let me provide some highlights of our fourth quarter and full year 2025. All comparisons are year-over-year unless otherwise noted. As a reminder, full year comparisons do not adjust for the 8 extra days in fiscal 2024. In 2025, we generated total revenue of $7.05 billion, up approximately 15%, which included $757 million of Ansys revenue. Q4 revenue was $2.25 billion, coming in at the high end of our guidance. Ansys Q4 revenue was $668 million. Geographically, China continued to be challenged, consistent with our commentary last quarter. China ended 2025 down 18%. Excluding Ansys, China was down 22% this year.

2025 total GAAP costs and expenses were $6.14 billion, and total non-GAAP costs and expenses were $4.42 billion, resulting in a non-GAAP operating margin of 37.3%. Q4 GAAP costs and expenses were $2.13 billion and total non-GAAP costs and expenses were $1.43 billion, resulting in a non-GAAP operating margin of 36.5%. Q4 and full year 2025 GAAP earnings per share were $2.39 and $8.07, respectively, which included the gain on the sales from the recent divestitures. Q4 and full year non-GAAP earnings per share were $2.90 and $12.91, respectively, ahead of our guidance on lower expenses.

Now on to our segments. Full year 2025 Design Automation segment revenue, which includes EDA, Ansys and other, was $5.3 billion, up 26%. Excluding Ansys, Design Automation revenue grew approximately 8% with steady growth in EDA software and a record year in hardware. Design Automation adjusted operating margin was approximately 42% in 2025.

Full year Design IP segment revenue was $1.75 billion, down 8% due to the challenging second half with the headwinds highlighted last quarter. The IP business performed in line with our revised Q3 expectations. Design IP adjusted operating margin was 24% in 2025.

Moving to cash. Free cash flow for 2025 was approximately $1.35 billion and came in ahead of expectations, primarily due to the accelerated timing of collections. We ended the quarter with cash and short-term investments of $2.96 billion, which includes approximately $600 million in proceeds from the sale of the Optical Solutions Group and Ansys PowerArtist business. Total debt ended at $13.5 billion. We repaid approximately $850 million of our term loans in Q4 '25 and $900 million in November and plan to prepay the balance of $2.55 billion in the first half of 2026. We have incorporated this in our guidance that I will now discuss.

For 2026, the full year targets are total revenue of $9.56 billion to $9.66 billion. Within that, Ansys revenue contribution is expected to be $2.9 billion at the midpoint, growing double digits. Following the close of the Optical Solutions Group and PowerArtist divestiture in October, our fiscal year '26 guidance excludes revenue associated with those groups, resulting in an impact of approximately $110 million. We expect the first half, second half revenue split to be approximately 48% and 52%. We expect Ansys revenue to be strongest in Q1, given their historical strength in the December quarter driving the sequential revenue increase.

Total GAAP costs and expenses between $8.47 billion and $8.61 billion. Total non-GAAP costs and expenses between $5.69 billion and $5.75 billion, resulting in non-GAAP operating margin of 40.5% at the midpoint, up approximately 320 basis points versus 2025, driven by the inclusion of Ansys and cost synergy acceleration. We are adopting a normalized non-GAAP tax rate of 18% projected through 2028 to provide consistency across future periods. The 2-point increase is driven by geographic mix of earnings inclusive of Ansys and recent tax law changes. GAAP earnings of $2.49 to $2.90 per share. Non-GAAP earnings of $14.32 to $14.40 per share. We expect the first half, second half EPS split to be 46-54 with the second half benefiting from the debt repayment.

Cash flow from operations of approximately $2.2 billion, up approximately $700 million year-on-year. The cash flow guide includes the impact of certain nonrecurring outflows, such as restructuring costs of approximately $225 million and $135 million of incremental cash taxes from recent divestitures. We expect CapEx of approximately $300 million, up $130 million versus 2025, driven by investments primarily in compute infrastructure, resulting in free cash flow of approximately $1.9 billion. Fully diluted shares outstanding are expected to be between 192 million and 194 million shares. This includes the impact of the recent share issuance to NVIDIA as part of our strategic partnership. With our plans to accelerate our term loan repayment, we expect the net impact to be accretive to EPS in fiscal year 2026, which is incorporated in the guidance.

Now to targets for the first quarter. Total revenue between $2.365 billion and $2.415 billion, total GAAP costs and expenses between $2.165 billion and $2.23 billion, total non-GAAP costs and expenses between $1.395 billion and $1.425 billion, GAAP earnings of $0.22 to $0.41 per share, and non-GAAP earnings of $3.52 to $3.58 per share. Our press release and financial supplement include additional targets and GAAP to non-GAAP reconciliations.

Before we take your questions, I'd like to reiterate our focus on driving sustainable growth and margin expansion through unmatched innovation and disciplined execution. 2025 was a transformational year that redefined Synopsys. In 2026, we will expand our position as a leader in engineering solutions from silicon to systems.

With that, I'll turn it over to the operator for questions.

[Operator Instructions] The first question today will come from Jason Celino from KeyBanc.

Great. Maybe my first one for Shelagh. The embedded organic growth rate in the 2026 guide, I don't know if there's a way for us to understand what that might be and what that might imply for IP growth. I'm okay at math, but I'm just a sell-side analyst. I mean, if we adjust for the Ansys and the divestitures, I'm getting like 8% growth organic. I asked the question because I'm just trying to understand the level of conservatism.

Yes, it's definitely in that ballpark. And I think two things that I would highlight. One is, and I had it in my prepared remarks, we did have the disposition of the Optical Solutions Group and the PowerArtist Group, it's $110 million. So that's about 1.5 points. So just point that out to you. And as we talked about in Q3, we do anticipate a muted year of growth for IP. We are very much well into repositioning workforce to build out the HPC title so that we've got those fully available for customers. But we do expect the group to be in transition this year. And so we factored in muted growth for the IP business. So you're seeing that. And as I talked about, Ansys, our guide for Ansys is $2.9 billion at the midpoint, and that's double-digit growth for Ansys. So we're trying to be pragmatic with our forecast in light of the body of work that the IP team needs to do in '26 to be able to get us back to the long-term growth rate in IP.

Okay. And then the operating margin EPS guide is pretty fabulous even when considering the extra dilution from the NVIDIA investment. I don't know if I heard you talk about a specific synergy number, but curious if there's any extra details there.

Sure. So one of the things we had talked about last time that we're well on way to do is the 10% workforce reduction. That encompasses a body of work that we've been doing on synergies. We've already done an action in November time frame. We anticipate that we're largely complete with that in 2026. So we're very much on the path of working to accelerate those synergies as quickly as possible. And as you know, Jason, we've been very focused on driving margin expansion over multiple years with this guide. It's about a 12-point margin expansion since 2020. So we're very focused on that, very focused on driving both sustainable growth and expansion of margin.

The next question is from Harlan Sur, JPMorgan.

If I exclude Ansys to the person that asked the question before me, the core EDA plus IP is growing about 8%, 8.5% year-over-year in the fiscal year guidance. Can you just help us understand what you're embedding for growth in EDA and IP in the guidance? For example, if I assume IP is growing modestly, as you guys say, let's say, 5%, then your EDA business is growing around 9%, which is still below kind of your forward target of like 12%, 13%. Is that kind of the way to think about it? And if so, like why is the EDA business still undergrowing your long-term sort of forward target CAGRs?

Yes. Thank you, Harlan, for the question. Your math is in the ballpark. What we're taking into account for the EDA growth because on IP, you captured it well, we're guiding a muted growth for IP. In EDA, we're taking a couple of things into account. One, the China environment, where the cumulative impact of restrictions is something that we are seeing and have seen in '25 that has had an impact is different than, say, 2020-21 time frame where many start-ups and a significant spending was happening in China. And the other factor is we're still operating in a tale of 2 markets. There are a number of companies that they are building chips for industrial, automotive and anything outside the AI infrastructure build, their road map is somewhat muted. They're not driving at the same pace as what we're seeing with the other group of customers that they are delivering chips for the AI infrastructure.

Then, as you know, with EDA, there are a number of components. There is the software and the hardware-assisted verification. On HAV, we continue on seeing a significant demand due to the complexity of verification. The long-term view is double digits, but that's what we have took into account in terms of the guide for '26.

And the other thing that I would add, that's just a mechanical item, Harlan, is the divestiture of the Optical Solutions Group and the PowerArtist Group. So that's a $110 million headwind. But that's just a mechanical thing just to add that into what's being outlined.

Got it. No. Got it. That was insightful. And then Shelagh a question for you. Total expenses exiting Q4 was about $1.43 billion. You're guiding that to roughly about $1.41 billion in the first quarter. But if I look at your average quarterly expense run rate through the year on the full year guidance, it's still averaging about $1.43 billion per quarter. So it kind of doesn't seem like there's much in the way of synergy unlock in fiscal '26? Or are cost synergies being offset by increased spending in other areas? And where do you expect the total expense to be run rating sort of exiting fiscal '26?

Yes. So our commitment on the cost synergies, you're really seeing that flow through kind of back to Jason's question on the op margin, the 40.5%. Obviously, we've committed to mid-40s long term. So we're well on the way to that. And when we think about kind of the profile of expense structure, it is changing a little bit just because of the ingestion of Ansys as to how the quarterly splits run. But our expectation is throughout the pace of the year, we're going to continue to have reductions in workforce. But we're still going to focus our main investment on driving innovation and driving the road map. And so the reductions will still allow us to have significant investment in R&D.

Next up is James Schneider from Goldman Sachs.

I was wondering if you could maybe give us a bit of an update on the IP business and your expectations you laid out last quarter around some of the headwinds that you're seeing, whether that be your foundry customer, China and the execution on custom IP blocks. Can you maybe give us an update on sort of the level of progress you've had in each of those 3 dimensions? And how that sort of plays into the overall IP outlook for the year? Do you expect it to be sort of low single digit or you think mid-single digit is possible?

Thank you, James. I want to start with, as we zoom out, my confidence in our long-term mid-teens for our IP business only gets stronger. I know when we talked 90 days ago, we have focused on some of the headwinds. But the overall strength of the portfolio we have is such a privilege to have the portfolio as we engage our customers in various markets, not only AI, HPC because as you know, the market of semiconductor is much broader. Today, we are the leader in providing the IP for automotive, for mobile, for many other segments. In the AI HPC, we have a very strong position. And our customers constantly are reminding us how mission critical we are to their road map and development.

We outlined 90 days ago 3 headwinds: China and the whole foundry update, we're assuming in our guide that not much change going into FY '26. In other words, we are being balanced and pragmatic the way we're taking into account in our guide for IP, these 2 factors. In terms of resources and prioritization, we made a number of changes. We made changes in our development leadership. We made some changes in the sales leadership as it relates to IP. And we are well on our way to close some of the gaps you're going to see from a customer engagement point of view on some couple of the titles that we are being pressed on timing of delivery is that we will close these gaps by midyear '26, FY '26. So all in all, we're looking at '26 as a transitional year, muted growth with the long-term objective of mid-teens, and that we feel very strongly about.

That's helpful. And then maybe just as a follow-up, obviously, last week, you had your announcement of the NVIDIA partnership and the investment in the company. Can you maybe give us a little bit more color on sort of the rationale for why an investment made sense? What could have been done with an investment that couldn't have been done simply through a strategic partnership and maybe kind of walk us through the logic around that?

Sure. I'm happy to walk through how it ended up being an investment where the discussion started with NVIDIA is enthusiasm and excitement about the new Synopsys, the silicone to systems engineering solutions that addresses not only the silicon part, it's going up to the whole physical AI and delivering solutions to the future of engineering in every industry. So the discussion with NVIDIA started around how do we accelerate at the computational level with the GPU, and that's something that is already a number of our products. We have a road map for that acceleration. Then it went up to the Omniverse level, how to modernize or the way we refer to it, how do we reengineer engineering for intelligent systems? And this is where the Ansys portfolio is very unique as they bring in a multi-physics simulation leadership to bring that physical simulation physical AI into effect and providing that modernization of engineering.

The third element is our go-to-market reach. Ansys has built a very strong channel partnership and direct sales channel that we touch thousands and thousands of customers in many industries. So as the discussion with NVIDIA started evolving on defining the technology partnership, the discussion with Janssen moved to, I want to endorse it with investment because I know we can make money. And I know you heard his own words as we announced the partnership. So the financial aspect was second because as you can see, we have a very strong balance sheet. And we welcome the $2 billion investment. And as Shelagh outlined, we will accelerate some of the debt payment and help us with accelerating some of the strategy we have. So that's how it really came about.

The next question comes from Kelsey Chia from Citi.

So I'd like to tap on the EDA growth rate again. So you mentioned that the lower EDA growth in fiscal year '26 is due to slower chip design momentum in China. Is that the same reason for the lower growth rate this year as well? And are there any share shift dynamics happening over there? And if synergies with Ansys could drive that revenue growth back to target?

Yes. As it relates to China, there is some share shift happening inside China because when you restrict the sale of EDA or IP, the customers in China are looking for alternatives. And that is happening, and it's happening at an accelerated rate. The customers we can serve we're fine selling to and they're buying from Synopsys or other that the companies we cannot sell to, they're looking for alternatives, and these alternatives are typically organic, local, EDA or IP companies.

In terms of the longer-term growth opportunities for EDA, and that's why we're still standing behind double-digit growth for EDA is going to come from the joint solutions between Synopsys and Ansys. We are targeting the first half of '26 to deliver the first wave of these solutions. There is the need for customers -- from customers to address the current challenges they are facing as they're designing the most advanced chips, advanced package, 3DIC, where they need the physics analysis to be taken into account during the design phase of the chip. And this is something we're very excited about. The team is already working toward the goal of delivering the first wave of the solution, and that's a monetization opportunity. But of course, that opportunity in terms of monetization will happen over time as customers adopt, et cetera.

The second monetization opportunity is as the Agentic AI solution start maturing and start changing the workflow, that's another opportunity for our industry to rethink how do we sell our solution for the value and impact. So again, the China impact, we're taking it into account in our guide and the upside opportunity as we look at the long term is joint solutions and the AI changing the workflow.

Got it. So on the IP business, so I know that Synopsys provides several IP for a large foundry customer, including the EMIB advanced packaging technology, it seems that there are several customers evaluating that, using that technology from a large foundry customer. Will that be incrementally positive for Synopsys given the muted growth that you have provided? And also relating to that on the operating margin, I believe are the expenses related to those IPs have been consistently recognized over the prior quarters despite the lack of customers. So does that imply that operating margins for that segment could trend back to historical average when the revenue for that large foundry customers are being recognized?

Yes. Let me address the first part of your question, then I'll turn it to Shelagh. The way we monetize our IP, the first step is to build it. And what you build on foundry A is not the same on what you build on foundry B, even though it's the same protocol, the same title. It does require what's called porting. And that's not a simple effort. It requires quite a bit of an R&D effort to achieve the same performance, power, et cetera. Now that's one part of the monetization. But where we look for the incremental monetization is when that foundry start on ramping customers. And if whichever foundry has expansion of customers that are using the technology that we already developed the IP, that's an incremental opportunity for us. And there, we sell to the end customer who is on ramping to the foundry customer. And for us, we're -- as we're looking at FY '26, for that particular foundry that we talked about in Q3, we're assuming a status quo in terms of new customers being on ramp.

Shelagh, if you want to address the operating margin?

Yes, sure. So in terms of operating margin, Kelsey, you're right. We still are investing in building the titles out. We've repositioned the workforce to be able to build the HPC titles up, as Sassine talked about, and so it is really -- we're going to have muted growth in '26, which will mean there will be some pressure on the operating margins. But as we get back to that mid-teens growth long term, we'll see expansion in the margins. And I do expect that IP margins are always slightly below the corporate average because it's such a people-intensive body of work to deliver but it's really a short-term effect just because of the kind of the headwinds on revenue of the op margin challenge through '26 on IP.

We'll now here from Siti Panigrahi from Mizuho.

I want to drill into the Ansys. Double-digit growth for next year is pretty good. So I would love to hear what's baked into that in terms of assumptions there? It's been now more than 4 months since you've closed Ansys. Do you expect, in terms of business model or contract, which are different, do you expect them to convert to subscription? And if you do so, what kind of uplift or any kind of multiplier effect we should expect there? And Sassine, in terms of integration, where are you so far? Any color would be helpful.

Sure. Thank you, Siti, for the question. In terms of what's driving our confidence in double-digit growth for Ansys, the way we look at it, there is two markets we're serving with the Ansys portfolio. There is the semiconductor market that the joint solutions will bring an opportunity to uplift our pricing as we integrate the Ansys solution into the EDA solution that we offer today. Then the rest of the Ansys market, if you look at the significant transformation that's happening on how to develop a modern car, robot, any industrial applications, drones, et cetera, aerospace, those are all customers of Ansys. And the demand, the increase in R&D investment that we are seeing in those markets is giving us the confidence to continue on expanding the growth opportunity.

In terms of the business that Ansys has, they've always had a mix of subscription and perpetual. And that will continue based on the customer need, requirement, demand. So that's what's driving the double-digit growth assumption for the portfolio, which, by the way, is no different than what the legacy Ansys team has delivered in the prior year. So it's consistent, in line with prior expectations.

In terms of integration, since we finalized the divestitures in October, we're full force ahead in terms of integrating the teams. Our R&D teams right now, they're one team. They're delivering on the joint solutions I just mentioned. From a go-to-market point of view, we are maintaining a separate go-to-market engagement. The one that they deal with semiconductor. Those are integrated given the relationship Synopsys has with semiconductor companies. And the slew of other customers, and I'm talking multiple factors larger than the classic Synopsys in terms of the space that the legacy Ansys has served, that will remain separate. So we don't miss a beat in terms of how to go to market with the existing portfolio that we have.

Yes. And I would just add, Siti, that the portion that Sassine talked about of Ansys that's in lockstep with the EDA business, that is moving to a similar ratable, and that's included in our guidance.

Okay. And then I just want to clarify that we need the same customers now using Synopsys PD and Ansys. When you launch your combined product, should we expect any kind of uplift there? Or what kind of uplift should we expect? I mean, is that 1 plus 1 will be more than 2 or less than $2 there? And Sassine, quickly, any update on that royalty model for IP, you talked about, any traction you're seeing?

Sure. Yes. When we talk about joint solutions, the customers have the options. They have the choice. If they don't have a need for that new joint solution, they can continue buying the classic Synopsys and legacy Ansys products, and we'll negotiate those based on value and usage and need, et cetera. If the customer is looking for the joint solutions because we're solving a new problem, 1 plus 1 is greater than 2, for sure. And that's where we will capture that monetization opportunity over time as they start adopting the technology. As I stated, the first wave where the customers start using, feeling the technology and evaluating it is the first half of '26.

In terms of the IP value capture, the focus we put together in Q4 that I'm very pleased with. We looked at it from, I want to say, 2 pathways. The first one is just the discipline in pricing and guardrails because we have a differentiated IP portfolio. And I was very pleased with the go-to-market team in monetizing around the newly established, I want to say, guardrail and disciplines we put in place. Then the second aspect of it, and that's where we spent quite a bit of time 90 days ago talking about, there's an increase in customization in IP. And we are having discussions with a number of strategic customers that we're happy to allocate resources to deliver on that work, but we need to change the business model from an NRE plus a use fee to NRE plus use fee plus royalty and upside. And these discussions are happening, and I feel very good that in FY '26, we'll be able to lock up some customers in that new business model where they see the value of bringing that customization and portfolio to their road map.

[Operator Instructions] We'll go next to Vivek Arya from Bank of America.

For the first one, Sassine, I'm trying to gauge whether the IP business is derisked because if I look at your Q4 IP, and I just annualize that, that's about $1.6 billion and change. But if I assume that it grows modestly, that's more like $1.8 billion, right, or so. So from a year-on-year perspective, it seems derisked, but off of Q4 levels, not as much. And I wanted to get your sense, is that a fair pushback? Just how are you thinking about the sequential recovery in your IP business? And if Shelagh, you have a number for Q1, that would be very helpful also.

Yes. I really urge you not to look at it at -- from a quarter basis because the IP business, as we often refer to, is -- can be lumpy. I am very confident, very confident in our portfolio as well as the market position we have. We were very transparent in Q3 that there were a couple of titles that we needed to do some work to accelerate our road map to deliver to customers. And for those titles, we're having ongoing customer -- ongoing engagement with the customers with our revised road map. And I have no doubt that we will capture the opportunity for these couple of titles. The rest of the portfolio is performing incredibly well. So yes, I feel very good that we have derisked the headwinds that we communicated last quarter as we look into '26.

And Vivek, what I'd give you with a sort of flavor for the year is IP will be back half loaded. And that's really got to do with the availability of all the HPC titles. So the team is actively working, hitting all the milestones to be able to deliver that, but a few of them are not going to be available until the second part of the year. And so that's really kind of how we built the forecast. As Sassine said, the demand is there from the customers and very solid, but some of our delivery is more back half weighted.

Understood. And for my follow-up, what are you assuming for your China sales and on an absolute dollar basis relative to the $814 million or so that you're doing in fiscal '25? And I guess, Sassine, the broader question there is, can your EDA and IP business get back to double-digit growth if you continue to see these China restrictions or if you kind of proactively derisk your business from China engagements?

Thank you, Vivek. So we expect the environment to remain challenging in China. That's why when we look at FY '26 compared to '25, what we are taking into account in our forecast and guide is truly a pragmatic balanced view. We're not assuming that the environment is going to change in the next 1 or 2 quarters to the positive. So therefore, we continue on derisking it in our guide for FY '26.

In terms of the double-digits growth for EDA, we still feel strongly about the opportunity to achieve double digits on the -- from a long-term basis, and it's driven by the complexity and the need for the joint solutions. And as AI evolves from generative to agentic, it will change the workflow, and that's a great opportunity for our industry to find a new way to monetize for the value that we will be delivering to the customers. So again, from a China point of view, we continue on derisking with an assumption of the environment remains the same. And the long term for EDA double digits is something we were holding for that commitment.

The next question is from Joe Vruwink from Baird.

I just wanted to stay on the IP topic and given everything that's come up so far in terms of the titles you're seeking availability on midyear and some of the other like strategic elements, the custom IP and potentially changing the business model. That midyear time frame, would you expect to know by then the magnitude of commitments you have in hand so that FY '27, you can maybe make the statement, it will be back to mid-teens growth. I guess my question is mid-teens growth, is that capable for FY '27 based on the pipeline of opportunities you see today?

Yes. Just let me clarify the midyear. We're not waiting for us to talk to the customer until midyear, we talk to the customer, we have active engagement and even in contract phases with customers based on their road map and based on our road map of delivery. We have established very strong trust with those customers, and they build their road map based on our ability and delivery.

So the other thing I'll point out in terms of IP and in general is the strength of the backlog we're entering the year. Entering the year at $11.4 billion in backlog, that shows the strength of the bookings, the commitment we've had with customers, and it's all about execution and delivery. So Joe, in general, as I keep repeating, my confidence in our IP portfolio is driven by the discussions we're having with customers and the essentialness of what we're delivering here.

Okay. I guess I'll next ask about cash flow performance. I look at your adjusted EBIT margins better than 40%. That's nearing the mid-40 goal. Cash flow, I think the guide implies something closer to 20%. So obviously, a lot of upside still to the margin framework there. Just would you expect some of these onetime cash items, restructuring, do those start to settle out of the model as we think forward into the out years?

Yes, absolutely, Joe. That's why I called them out because I very much think they're onetime, kind of one-off items. The two that I called out was the restructuring. And then obviously, as a part of the OSG, PowerArtist, there was a gain. And so there's the tax on the gain, but those are not recurring. And we're very much focused. That's a $700 million improvement year-on-year. We're very much focused on driving to that long-term commit of unlevered free cash flow in the mid-30s margin.

Charles Shi from Needham & Company has the next question.

Sassine, maybe a question for you, a little bit longer term, a little bit beyond fiscal '26. A lot of the pushbacks I'm hearing from the investment community on Synopsys and actually not just the Synopsys, but the entire EDA industry, entire group is AI is doing very well, but the sector you're in continue to show -- I mean, continue to show deceleration, I would say, since 2022. And it's kind of hard for a lot of folks to understand, given you have all the exposures to all the AI players there, but your business didn't really turn up over the past few years. Is that a monetization problem? And if yes, how do you plan to solve the monetization problem?

Charles, if I understood your question correctly, when you look at the AI from a semiconductor road map development point of view, it continues on being very strong. If you're a hyperscaler and pretty much every hyperscaler, they're -- they have 3 parts to satisfy their infrastructure build-out. They're buying merchant chips, they're engaged in ASIC and pretty much each one of them, they have their own COT, where the customer own tooling, where they're developing their own semiconductor chips. And the reason they are counting on all 3, it's because of the optimization they need to do for different workloads from a cost and power consumption and the overall ownership of the consumption, it makes sense for them to have a strategy based on these 3 vectors.

From a Synopsys point of view, that's a great opportunity because remember, we don't sell based on volume. We sell based on chip start. So if the chip is coming from a merchant or coming from ASIC or the customer themselves building it, for us and the industry, that's an upside. So we don't see that changing actually, and we see these hyperscalers are doubling down on that strategy.

Yes. So Sassine, maybe I should make my question clear because I think all the trends you described, I think that's pretty well understood. But at the same time, folks who are looking at your revenue growth, especially the EDA IP part, maybe not just the Synopsys, but also Cadence and some of your peers. This whole EDA/IP industry seems to have quite a bit of a deceleration, a growth deceleration over the last couple of years. So this is a kind of in the opposite way of semis, which has seen a very strong AI uplift. So kind of led us to kind of think maybe you -- what the problem you have is not exposure, not that you don't have exposure to AI, but you have a little bit of difficulty to monetize AI. And I think one of the things you mentioned about maybe opening up a third avenue of monetization for IP business, basically for getting into the royalty is the right direction. But we're still kind of curious what do you do about that on the EDA side. It has been a segment that's kind of growing in the single-digit range for a couple of years. It looks like it's going to be another single-digit growth year again.

Yes, Charles, thank you for clarifying. Absolutely, as an industry, we can do better in capturing more value for the impact we're delivering to our customers. No question. Given the complexity of these chips, what these customers are building, it's not possible without Synopsys and the industry to deliver to the complexity of what we're building. If you look at it from an EDA point of view, the hardware part of EDA is growing at a pace that each year we're saying we're breaking the prior record. And so customers are willing to pay in order to deal with that complexity.

On the EDA software, there is a challenge in terms of the inflection point of monetization. From a Synopsys perspective, every one of these advanced customers are looking for that joint solutions between Ansys and Synopsys. That's an opportunity 1 plus 1 to be greater than 2 as we move to a different workflow for agenetic AI, that's another opportunity for the industry to rethink how do we sell that solution.

From an IP standpoint, the conversations are happening. And that's why when we talked about it 90 days ago, we were talking about it from a position of strength and an opportunity that those customers are expecting and wanting to engage differently. And we're having the right conversations right now to say we're happy to do it, but we need a different monetization upside for these engagements. So good observation, Charles, and I hope my -- the way I'm describing where we've been, where we are, where we're going, it's giving you confidence and shedding some light to it.

And our final question today comes from Ruben Roy from Stifel.

Sassine, you spent a lot of time talking about China, but I do have one question on sort of where you are with China revenue, still meaningful exit rate around 10% of overall revenue. And I'm wondering if you could talk about the mix there and if the headwinds that you're sort of seeing in the pragmatism is across the mix. Meaning, is it core EDA plus IT plus hardware and Ansys? Or are there specific areas that you're more concerned about as you think about this year or even longer term relative to China? And I guess I'm trying to get to, is this a reasonable floor once you get past maybe some of the IP issues that you have there? Or are there other shoes to maybe drop in China as we think about the longer-term model?

Yes. Thank you, Ruben. I want to clarify, and I know Shelagh mentioned it in her prepared remarks, the Synopsys classic had a decline in China. The Ansys portfolio performed fairly well in China because they sell to a very broad market that is not restricted. And we believe a lot of those customers will continue on seeing the value in the legacy Ansys portfolio, and that will continue on growing.

On the classic Synopsys side, what we're facing in China is primarily our inability to sell to our -- to the market that needs the most advanced solution. And you're familiar, not only with entity list, but with technology restrictions. From a Synopsys standpoint, where it impacts us the most is in IP, given the proportion of our business and our leadership in IP, not only in China broadly, but in China that has a fairly big impact on Synopsys.

From EDA in general, as I answered it earlier, we're not losing share to our standard or the peers that you think about when we're losing share in China are for customers our industry cannot sell to. And therefore, there's an erosion that is happening on the EDA side on customers that we cannot deliver or support due to entity restriction or technology. So we believe we have derisked it in our guide for '26. And of course, when you pass '26 and assuming the environment is the same, meaning no additional restrictions, then the comps get easier in terms of comparing year-over-year.

And everyone, that does conclude our question-and-answer session. I would like to hand the conference to Tushar Jain for any additional or closing remarks.

Thank you all for joining the call. We look forward to talking to you during the quarter and meeting you at CES. Lisa, you can go and close us out. Thanks.

Thank you.

Thank you.

And once again, everyone, that does conclude today's conference. Thank you all for your participation today. You may now disconnect.