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Good day, and thank you for standing by. Welcome to the Rackspace Investor Conference Call. [Operator Instructions] Please be advised today's conference is being recorded.

I would now like to turn the conference over to Sagar Hebbar, Head of Investor Relations. Please go ahead.

Good morning. I'm Sagar Hebbar, Head of Investor Relations. Joining me today are Gajen Kandiah, our Chief Executive Officer; and Mark Marino, our Chief Financial Officer.

As a reminder, certain comments we make on this call will be forward-looking. These statements involve risks and uncertainties, which could cause actual results to differ materially. A discussion of these risks and uncertainties is included in our SEC filings. Rackspace Technology assumes no obligation to update the information presented on the call, except as required by law. In particular, our discussion today will include forward-looking statements regarding our recently announced definitive agreement with AMD, including, without limitation, the ability to dedicate, maintain and make available an aggregate of 30 megawatts of AMD products contemplated by the GPU as a Service agreement, which may not be achieved in full or at all or may be achieved on a materially different time line.

The anticipated benefits and performance of GPU and CPU compute deployments, the expected delivery of enterprise AI cloud, Enterprise Inference Engine, inference as a Service and bare metal AMD instinct capabilities, anticipated end customer demand, the expected commercial and financial benefits of the collaboration to each company and the parties' respective outlooks on the AI industry.

While the parties have executed a definitive agreement establishing a commercial framework for the collaboration, individual deployments authorizations are subject to separate execution and certain commercial terms, including pricing and financial parameters remain subject to further agreement between the parties. AMD has no obligation to agree to any particular deployment as being within the scope of the framework. Any third-party financing required to implement planned deployments is subject to availability on terms acceptable to the company.

The GPU-as-a-Service agreement is subject to certain financing, operational and legal conditions and provides AMD with the right of first refusal that may affect the company's flexibility in selling capacity to third parties. There can be no assurance that deployments will occur on the anticipated time line that financing will be obtained that AMD will agree to future deployments or that the anticipated benefits of the collaboration will be realized.

Deployments are subject to the availability of and lead times for AMD products from third-party original equipment manufacturers. Our discussion will include forward-looking statements relating to the company's workforce realignment plan, including without limitation, the expected number of employees affected the anticipated timing and implementation of the reduction in ports across jurisdictions. The estimated onetime expenses associated with the workforce realignment plan and the anticipated Bruce annualized savings reinvestment plans. Actual expenses, savings and reinvestments may differ materially from these estimates as a result of changes in the scope, timing or implementation of the workforce realignment plan, variations in severance obligations across jurisdictions, the timing of employee access, regulatory or legal requirements applicable in certain jurisdictions, certain or actual litigation and other factors.

There can be no assurance that the company will realize the anticipated savings from the workforce realignment plan within the expected time frame or at all. The company undertakes no obligation to update or revise these forward-looking statements, except as required by law.

With that, I will hand the call over to Gajen.

Thank you, Sagar. Good morning, everyone. We are announcing 2 items this morning. First, we have signed a definitive agreement with AMD to deploy 30 megawatts of compute phased from late 2026 through 2028. Second, we are bringing the company together to go to market as one Rackspace. One company with our people and our investments pointed at the same strategy we've been building towards. Rackspace is rebuilding itself as the operator for governed enterprise AI designed around how production AI is deployed operated and scaled inside regulated enterprises.

The AMD agreement further demonstrates this shift. Today's announcements are intentionally concurrent. Infrastructure without an operating model is capacity an operating model without committed infrastructure is expiration. Together, they established a scalable platform for disciplined growth. This is not a course correction. We have been deliberate about sharpening our strategy and executing with greater focus and accountability. Unifying as one Rackspace is the alignment of our structure to that strategy. The AMD definitive agreement is proof that the market is responding to the choices that we've been making. Focused efforts clear accountability and an integrated company designed to move enterprise AI into production, reliably and at scale.

Enterprise AI has advanced beyond the experimental phase. Agentic workflows are now embedded in production systems across banking, health care, energy and government. These are regulated mission-critical environments where governance, data sovereignty and operational continuity by not selling points, they are the price of entry. Customers are no longer asking where they can access the compute. They're asking which operator can govern AI responsibly, securely and at scale inside their organization. The hyperscaler delivers compute, a systems integrator deliver services. Neither is accountable for government AI in production end to end. That is the gap Rackspace is built to fill. We believe Rackspace is uniquely positioned to answer that question through trusted customer relationships, deep operational expertise and a global infrastructure footprint. Increasingly, Customers also want to avoid dependence on any single model of provider.

For us, this is not a future capability. We operate a model agnostic stack in production today. Customers run and switch the models they choose through a single orchestration layer, our context-aware inferencing keeps their domain knowledge and section context intact across that switch, and we own the SLA across whichever models they run. If a model becomes unavailable or no longer fits the workload, the customer is not stranded because the orchestration and the context sit about any 1 model. That is the continuity of government-operated delivers and the hyperscaler or an integrated is not.

Today's agreement is the latest in a deliberate sequence of partnerships and each 1 is a building block in the same strategy. With Unifor, we deliver enterprise AI applications running in production in our private cloud, on infrastructure we operate and remain accountable for. With Palantir, we entered a strategic partnership in February and are building a Palantir-certified forward deployed engineering capability across foundry and AIP. And now with AMD, we secure the accelerated compute foundation beneath all of it. Our partners bring leading technology and Rackspace integrates it, operates it and remains accountable for it as a single accountable operator. The foundation beneath these partnerships is an enterprise-grade technology stack built for the demands of regulated production environments.

VMware serves as the control plane, providing the virtualization, workload portability and network fabric that governed enterprise AI environments require. Blue Brick provides the cyber resilience layer, ensuring that data is protected, recoverable and auditable across hybrid and multi-cloud environments, which is nonnegotiable in health care, financial services and suberin cloud. And our forward deployed engineers are the human layer that binds it all together embedded in the customer environment accountable after go live and the reason our SLAs are a commitment rather than a ton. This is the stack that differentiates Rackspace.

Every partner in our ecosystem sits inside a governed operating model that we own end to end, 1 operator accountable for the full stack. This model comes to life through 4 integrated capabilities, enterprise AI cloud, the enterprise influence engine, inference as a service and bare metal. Each is accelerated by the AMD agreement, which I will address directly. The delivery layer behind all 4 is forward-deployed engineering. Engineers who stay embedded in the customer environment and remain accountable after go live to ensure outcomes are achieved.

Since we established the public cloud business unit a few years ago, we have made significant progress building from an infrastructure-led operation into a services-led organization with deep capabilities across cloud delivery, platform engineering and managed operations. The capabilities we have built are the foundation we are building on. Our private cloud business has equally demonstrated the value of this model. operating some of the most demanding regulated workloads in health care, financial services and sovereign environments. With discipline, governance and accountability we have built in private cloud, is the operating template for everything we are now scaling across the enterprise AI platform. What has changed is where those capabilities need to be directed?

The customers we serve are moving from cloud adoption to AI in production. And that shift requires an operator who can manage the full stack end-to-end, not just the cloud layer. Our public cloud business is aligning to that imperative, concentrating investment on data and AI-led enterprise transformation, AI ops-driven managed services and forward deployed engineering talent that operates across hybrid environments from edge to core to cloud. This includes a reduction in our workforce, and Mark will take you through the details. This is the right decision and direction for Rackspace, and we are managing it with the care and the respect our Rackers have earned.

An integrated go-to-market strategy removes the fragmentation that can slow execution and strengthens the accountability our customers expect from a single operator end-to-end. The result is a company that is growing with discipline, investing in what matters exiting what does not and operating with the cost efficiency that long-term performance requires. We are not restructuring for growth alone. We are building a company that earns the right to grow by operating well.

Before I turn to the specifics of the agreement, I want to take a moment to recognize the team at AMD. This partnership with more than a commercial arrangement. It reflects a shared belief in where our governed enterprise AI should look like and who should operate it. We are grateful for the confidence AMD has placed in Rackspace, and we look forward to building this together.

The definitive agreement establishes AMD as a strategic technology partner at the silicon layer of Rackspace's governed AI stack. The agreement supports phased deployment of 30 megawatts of AMD AI compute capacity across Rackspace data centers with Rackspace functioning as the operator layer through which it is delivered. AMD selected Rackspace for this partnership because it speaks to what differentiates us. We have a global data center footprint with available capacity to support deployment, including the 30 megawatts contemplated under this agreement, which is committed and will be deployed in phases from late 2026 through 2029.

We bring more than 2 decades of operating regulated mission-critical workloads in health care and financial services, where we are already strong. We bring deep operational expertise in managed infrastructure at enterprise scale. And we bring a governed operator-led model. We do not simply resell compute we operate it and remain accountable for the outcome. That combination is difficult to assemble and it is what makes Rackspace the right partner to bring AMD Instinct into regulated enterprise production.

Initial deployments will be established across key markets with AMD Instinct MI355X and MI350P GPUs and AMD EPYC CPUs available for deployment across our data center footprint. The deployment model is capital efficient, leveraging existing infrastructure ordered upgrades and data center consolidation. We expect the initial deployment to commence in late 2026 and the balance of the contemplated 30 megawatts to be deployed in phases through 2028. We believe the demand environment supports this trajectory.

We are engaged in active commercial conversations across health care, financial services, public sector and energy weighted towards our existing enterprise customers where adoption cycles are shortened and cost is already established. Our near-term pipeline is anchored in this installed base and our intent is to match initial deployments to identify customer demand. Both Rackspace and AMD are committing dedicated sales and engineering resources to joint customer engagement. This is a go-to-market partnership, not a supplier arrangement.

This agreement accelerates 4 integrated capabilities. Enterprise AI cloud, our fully managed private and hybrid AI environment built on AMD Instinct accelerators with 1 operator accountable across the stack. Enterprise Inference Engine, a context-aware influence front time that retains domain knowledge, session history and enterprise-specific data context across queries with Rackspace owning the SLA. Inference as a Service, dedicated managed AMD Instinct compute as a governed alternative to commodity GPU rental and Bare Metal AMD Instinct for training and inference workloads requiring deterministic dedicated performance.

Strategic focus requires specificity. Rackspace has a clear path to win in regulated industries, health care, financial services and sovereign cloud as the government operator of Enterprise AI, and in private cloud and governed infrastructure environment. These are areas defined by our ability to deliver simplicity, accountability for outcomes and speed of execution at production scale.

Our credibility is demonstrated through what we already operate. Health care environments, including EPYC at scale, sovereign cloud deployments in the U.S. and U.K., strategic partnerships with Palantir and Uni4 both building towards the government enterprise AI platform and now anchored by the AMD definitive agreement that commits the compute foundation we need all of it.

With that, I will turn it over to Mark for additional financial context.

Thank you, Gajen. Let me provide context on the financial dimensions of this agreement. The definitive agreement establishes a base commercial framework governing 30 megawatts of AMD compute deployment commencing late 2026 and scaling through 2028. Deployment authorizations are executed in tranches, providing both parties visibility into the economics of deployment at scale. As we scale, we will provide additional transparency around key operating metrics.

We've identified multiple sources of financing who are supportive of this initiative, and we have confidence in our ability to secure adequate financing for initial deployments near term. We currently estimate that our first deployment will be approximately $50 million to $100 million of CapEx. As Gajen outlined, integrating our go-to-market focus is the alignment of our structure to our strategy, and that alignment has a financial dimension. In connection with this transition, we announced a workforce realignment plan that includes a reduction of up to 15% of our global workforce. This realignment is predominantly driven by the company's strategic decision to deemphasize certain legacy service delivery functions, primarily within its public cloud business unit and geographic rationalizations in favor of redeploying resources towards this Enterprise AI build-out.

We expect to incur onetime charges of approximately $14 million to $19 million in 2026. Following full implementation, we expect to realize approximately $75 million to $85 million in annualized run rate savings. A significant portion of those savings will be reinvested into our highest growth capabilities including forward deployed engineering, AI solutions delivery and enterprise AI infrastructure build-out. This is a deliberate reallocation of capital from offerings that are not aligned to our strategic priorities, towards the government enterprise AI platform we are building. We view this as a time-limited cost with a clear and measurable return.

I'll return the call to Gajen.

Thank you, Mark. Let me close with this. Over 2 decades, Rackspace has earned the trust of the world's most demanding regulated enterprises operating in environments where security, compliance, resilience and accountability are nonnegotiable. That institutional capability is not assembled overnight. It is not replicated by operators whose accountability ends at the infrastructure perimeter. The announcements we are making today reflect the convergence of a defined category, a unified company structure to capture it and committed infrastructure to execute.

We have sharpened our strategic focus. We are going to align how we operate to where we win. We have secured the first infrastructure commitment through our agreement with AMD. Our infrastructure, combined with our forward deployed engineers enables Rackspace to be the operator of government enterprise AI from silicon to outcomes. The demand pipeline is active and advancing. None of this comes without difficult decisions. Reducing our workforce affects real people who have contributed to building this company, and we do not take that lightly. We have an obligation to concentrate our people, capital and energy where we have the greatest path to succeed, and we are confident today's announcements position Rackspace to deliver for our customers, our rackers, and our shareholders.

Rackspace is the government operator for enterprise AI accountable from silicon to outcomes, operating at production grade, built for regulated industries where it matters most. One operator, full accountability. Thank you for joining us today. Back to you, Sagar.

Thank you, Gajen. Before we open the line, I want to focus our Q&A on today's announcement. We ask that participants limit to one question per caller. Broader financial results and guidance will be addressed at our second quarter earnings call. If you have any follow-up questions after today's call, please reach out directly at ir.rackspace.com. Operator, please go ahead and open the line for Q&A.

[Operator Instructions] Our first question coming from the line of Kevin McVeigh with UBS.

Congratulations on formalizing AMD. Really, really terrific context that you folks are able to offer. I guess just to follow up on that a little bit. Mark, I think you talked in $50 million to $100 million of initial CapEx. Any sense of when that's going to start to come in? And then if you're able to maybe reconcile that to the annualized run rate savings. And I know it's probably relatively abstract. But any way to dimensionalize what that 30 megawatts could mean from a cash flow perspective, EBITDA revenue? Just a lot of really, really good momentum? Just trying to frame it a little bit more in terms of impact on the model.

So Mark, let me go and Mark, you can chime in. Kevin, first and foremost, thanks for the question. Thanks for joining us. And again, I couldn't be more excited about announcing this agreement with AMD and also a massive thank you to AMD for their collaboration as we went through this process.

To answer your question, I think the way we've structured this, Kevin, again, going back to sort of who we are and how we operate. This is about how do we run AI in production, right, in enterprises and regulated enterprises. And so the way we have approached it is sort of through 3 different vectors, they're important before markets into his piece.

One vector is our customers themselves, sort of the customers we serve today and the customers that AMD has that we collaborate on together to go build the demand side or to capture the demand side is probably more appropriate. The second 1 is the type of workload. And that matters because in production or in inference, Customers are going to run across high-end GPUs as well as CPUs. And so understanding the type of workload and how to deliver that in the most efficient manner becomes really important.

And then third 1 is supply chain, right? And so when we think about the opportunity itself, it's less about demand and more about, I think, the type of demand and the and the supply chain that enables us to deliver the compute that is needed across that demand. So that then provides the context, I think, Mark, to kind of answer the question.

Yes. Thanks, Gajen, and thanks, Kevin. Yes. So as you can imagine, I mean, today, we're not going to be providing specific revenue guidance around the full 30 or that singular deployment, right? I think you can as you can imagine, you could look out a public data right now and see sort of well-established industry reference points around both what GPU as a service pricing in bare metal pricing? And just sort of keep in mind what this could mean for Rackspace, right? We're going to be playing in not just Bare Metal GPU service market here, but we're really moving up stack to enterprise AI.

So from a margin accretion and cash flow perspective, you'd be looking at a little bit higher throughput there. And then as we previously called out, 30 megawatts is existing capacity, existing power, right? So we'd be getting a nice fixed cost leverage, fixed cost or, if you will, related to those 30 megawatts. And just from a deployment perspective, depending on supply chains and timing, it is our intent to start receiving GPUs in the fourth quarter. I'd say no material impact to the financial statements this year, but certainly hit the ground running for next year.

Our next question coming from the line of David Paige with RBC Capital.

Congrats on getting this deal signed. You mentioned that the pipeline is the demand pipeline is very strong and active, so I was wondering maybe you could flesh that out a little bit more? And then maybe a quick follow-up. I know you said 30 -- the initial 30 million-megawatt footprint. Could you give us a better sense on maybe after 2028, I know it's far off from now, but how you see the business evolving through that.

Thank you, David. With regards to the demand side, if you look at our customer base, it's predominantly health care, financial services, energy and government. And picking health care, as an example, the demand is being driven by -- even within health care, if I said the provider as a specific subsegment. The demand is driven by clinical use cases, which are predominantly inference driven. And then there are, what I would say, R&D requirements, which would be a mix of compute -- sorry, training and inference.

And what we are seeing is that as the regulated customers begin to embrace AI and start to put it into production, there's very little capability in the market. But us and even -- I might even go as far as to say that we might be the only 1 that is looking at providing enterprise-grade government AI for these customers to run in a way where it is governed with data sovereignty and residency, which is critically important for these industries, David. So that's where the demand is coming from. So think of it as production demand, primarily driven by inference as well as some training.

And then there is also then our partner, AMD, who, again, they have their own set of customers coming to want to use their specific compute. And so that's another vector of demand that's coming in, which is why I feel that when you look at it through the lens of demand, that's less of the challenge. It's really about -- when you look at the supply side in terms of the compute, if you think about the networking, the memory, et cetera, it's just really trying to land the right type of compute environment and then ensuring that we can get it deployed within a reasonable time frame. So that's sort of the balance that we're working our way through.

And Mark, I'll let you pick up the 30 megawatts. Actually, I can answer it. On the 30 megawatts, a great question. I think, look, the way we have approached this, David, is to be thoughtful about how we ramp up the compute, right? I think the -- as you can imagine, the market is significantly dynamic. One thing that's happening is that we went from top and Maxine to Token efficiency in a 3-month window. And so I believe that it's our responsibility to deliver the most efficient token for the type of workload that's coming through. And to me, having both the customer work to understanding, having the partners like Palantir and Uni4 on the platform layer as well as then having an orchestration layer that is model agnostic and an inference layer that is context aware really allows us to manage a workload through the process to the most efficient token, if you will, or whether we are describing it.

And so I think once we get to sort of consuming this available capacity, if you will, once you become -- once we start to utilize that, we certainly have visibility to incremental compute. Again, keep in mind, we are inference not training. Therefore, the type of compute we need is different in terms of power, capacity, density, cooling, et cetera. So there is a lot more availability and we should be able to ramp up as and when that demand is needed.

And there are no further questions in the queue at this time. Ladies and gentlemen, that does conclude our conference call for today. Thank you for your participation, and you may now disconnect.

Good day, and thank you for standing by. Welcome to the Rackspace First Quarter 2026 Earnings Webcast. [Operator Instructions] Please be advised that today's conference is being recorded.

I'd now like to hand the conference over to Sagar Hebbar, Head of Investor Relations. Please go ahead.

Thank you, and welcome to Rackspace Technologies First Quarter 2026 Earnings Conference Call. I'm Sagar Hebbar, Head of Investor Relations. Joining me today are Gajen Kandiah, our Chief Executive Officer; and Mark Marino, our Chief Financial Officer.

As a reminder, certain comments we make on this call will be forward-looking. These statements involve risks and uncertainties, which could cause actual results to differ. A discussion of these risks and uncertainties is included in our SEC filings. Rackspace Technology assumes no obligation to update the information presented on the call, except as required by law. In particular, our discussion today will include forward-looking statements regarding our recently announced memorandum of understanding with AMD, including statements regarding the anticipated scope, benefits, commercial potential of the collaboration, deployment timelines or financial projections, the expected execution of definitive agreements and the anticipated impact of the partnership on our business, financial results and capital structure.

The MOU represents a nonbinding framework only and does not constitute a binding commitment by either party to complete any specific transaction, financing or other commercial arrangement. No definitive agreements with AMD have been reached. Discussions remain preliminary, and there can be no assurance that any such arrangements will be entered into, that the parties will reach agreement on terms or that the anticipated benefits of the collaboration will be realized. Any third-party financing required to implement the transactions contemplated by the MOU is subject to the availability of financing on acceptable terms. There can be no assurance that any such financing will be obtained.

Our presentation includes certain non-GAAP financial measures and adjustments to these measures, which we believe provide useful information to our investors. In accordance with SEC rules, we have provided a reconciliation of these measures to their most directly comparable GAAP measures in the earnings press release and presentation, both of which are available on our Investor Relations website.

I will now turn the call over to Gajen for an update on the business.

Thank you, Sagar. Last quarter, I said Rackspace was moving beyond being an infrastructure provider to becoming the orchestrator and operator of enterprise AI in regulated environments. We laid out 3 specifics: a partnership with Palantir anchored by a core build-out of forward deployed engineers, a technology stack with VMware as the control plane, Rubrik for cyber resilience, and Palantir as the data and AI platform layer, spanning infrastructure, resilience and AI and accelerating demand for Private Cloud in regulated environments.

The results this quarter reinforce the strategy we've been executing against what we call where enterprise AI goes to production, governed infrastructure as the foundation, an integrated technology stack of curated partners on top of it and one accountable operator running it end-to-end. Every win this quarter sits inside that frame. We secured regulated and sovereign Private Cloud deals across health care, telecoms and financial services. We also closed our first joint Palantir deal in 41 days, a U.S.-based solar tracking manufacturer where the problem was costly and quantifiable, 16.5 days to move from a customer inquiry to a signed quote, burdened by manual intake and fragmented handoffs.

Our FDEs deployed AI-enabled workflows on Palantir Foundry directly inside the customer's environment, reducing the quoting cycle by 94% and earning an expanded engagement to extend the FDE model into EMEA. We are also deploying Palantir inside Rackspace, running end-to-end business workflows on foundry natively. We are not just recommending Palantir to customers, we are operating our own business on it.

We continue to expand our partner ecosystem. Today, I'm pleased to announce the signing of a memorandum of understanding with AMD that establishes a new category of governed enterprise AI infrastructure. We are integrating AMD Instinct GPU accelerators, AMD EPYC CPUs and the ROCm software ecosystem into a fully managed governed technology stack, purpose-built for enterprise, including health care, financial services and sovereign environments where security, compliance and accountability are nonnegotiable.

The MOU establishes AMD as the launch silicon across our 4 integrated capabilities. Enterprise AI Cloud, our fully managed private, public and sovereign AI environment with one operator accountable across the stack, Enterprise Inference Engine, a context-aware inference runtime that retains domain knowledge, session history and enterprise-specific data context across queries with Rackspace owning the SLA; Inference as a Service, dedicated accelerated compute as a governed alternative to commodity GPU rental, launching with AMD Instinct; and Bare Metal Accelerated Compute launching with AMD Instinct for training and inference workloads requiring deterministic performance.

Production inference is heterogeneous. Frontier models run on GPU, small language models, classical ML embeddings and many domain-specific workloads run more efficiently on CPU. AMD is the partner that brings both Instinct GPUs and EPYC CPUs inside one integrated architecture, which lets us route each workload to the right compute. That is what production economics requires. This puts Rackspace in a unique category. The market today is dominated by commodity GPU rental, where capacity is sold by the hour and the customer carries the burden of integration, security and accountability. We are building the opposite.

AMD's leadership in open high-performance AI acceleration, combined with our operator-grade Outcomes-as-a-Service model delivers governed AI infrastructure that is accountable from silicon to outcomes. We expect the definitive agreement with AMD to be executed in the near term. Governed infrastructure is where enterprise AI either succeeds or stalls. When AI works with patient records, financial data or sovereign information, where that data sits and how access is governed determines compliance or exposure. That is why Rackspace's over 25-year history managing data centers and infrastructure is more important than ever. And this is why one of the largest EPYC environments runs on Rackspace.

The second reason enterprises choose us is how we handle technical complexity. Enterprise AI cloud is not a single component problem. It takes data, compute, models, small language models, inference and governance working together in real time. If even one element in the technology stack is off, cost per token skyrocket and operational risk increases. We solve this by integrating each vendor's IT, making technologies fit together and operate as one.

The third reason is accountability. In a fragmented enterprise AI cloud vendor ecosystem, nobody owns the outcome or takes responsibility when something breaks down. We solve that by being one accountable partner in the eyes of the customer, responsible for how the system performs and the outcome it delivers. That is why we are seeing momentum across the business.

At our core, Rackspace is a data center and infrastructure company. We own and operate the physical infrastructure that enterprise AI runs on. That foundation, combined with our ability to take end-to-end accountability for AI in production from governed Private Cloud to AI inference and agents in production is exactly what our enterprise customers are looking for.

And with that, let me get into our business performance, starting with Private Cloud. First quarter Private Cloud revenue was $235 million, with first half revenue on track with the timing of a large deal onboarding within our health care vertical, consistent with the dynamics we outlined last quarter. Segment operating margin came in at 24.7%, up 30 basis points year-over-year, driven by continued cost discipline. Our customer wins this quarter tell a consistent story. Enterprises in regulated industries are choosing Rackspace to modernize and operate environments where governance, reliability and compliance are nonnegotiable and where those environments increasingly serve as the foundation for AI adoption.

For example, in financial services, we secured a long-term recommitment from a leading global online trading platform, modernizing core infrastructure through software-defined Private Cloud, improving resilience and user experience in a latency-sensitive, highly regulated environment. In health care, we signed a multiyear agreement with a major U.K. NHS Foundation Trust to migrate and operate workloads in a sovereign health care cloud with full outcome as a Service and security embedded from the outset. And this quarter, we expanded our relationship with AdventHealth, a long-standing customer.

We already host and manage the infrastructure of their Epic EHR, one of the top 5 Epic systems in the world. And this quarter, we expanded our relationship to host and manage over 400 additional workloads on Rackspace Private Cloud. Health care is one of our most important verticals and one of the clearest expressions of our strategy. Epic Managed Services is proprietary Rackspace IP, purpose-built for governance, performance and uptime that clinical environments demand. As regulated health care organizations move from AI experimentation to AI in production, where data sits and how it's governed becomes the defining question. That is exactly the environment we are built to operate.

This extends into sovereign markets. In Saudi Arabia, our partnership with SDAIA places us inside one of the world's most advanced national AI programs, built on in-country infrastructure, jurisdictional accountability and managed operations.

In the U.K., BT recently selected Rackspace as the infrastructure foundation for BT Sovereign Cloud, positioned as U.K.'s first full suite of sovereign services hosted and operated entirely within the U.K. with security-cleared operations teams and managed services covering migration, operations and ongoing compliance. That is the kind of public anchor that validates our sovereign thesis. These are environments where AI cannot be deployed without full control over data and infrastructure, and they are increasingly central to how sovereign and enterprise AI is deployed.

What makes these environments possible at scale is VMware Cloud Foundation 9, the control plane at the center of our governed AI strategy. It unifies compute, storage, networking and security into one operating substrate with native AI workload support, data residency controls and policy enforcement that meets regulated and sovereign requirements out of the box.

Our deepening partnership with Broadcom around VCF 9 is one of the most strategic commitments we are making this year because it gives our customers a single control plane that travels with the workload with elasticity to Public Cloud where it makes sense. Running on top of that foundation is where our AI platform partnerships come to life. This quarter, we expanded our relationship with Uniphore, adding agent-based workflows to our governed AI technology stack. Together, we are building context-aware inference, a capability that retains domain knowledge, session history and enterprise-specific data context across queries. So AI agents and large language models perform with the consistency and institutional memory that production environments require.

Like Palantir, our engineers are trained on the Uniphore platform and embedded directly inside customer environment. We are not just orchestrating infrastructure. We are orchestrating outcomes. VCF 9 as the control plane, Dell for core infrastructure, Palantir and Uniphore for governed AI and agent workflows, Rubrik for data resilience, AMD for enterprise-ready compute. Each partner is best-in-class, but the value Rackspace delivers is making them operate as one integrated system with full accountability for how the system performs and the outcomes it delivers.

Looking ahead, the next phase is already emerging. As enterprise AI evolves towards agentic workflows where machines interact with machines and processes run end-to-end without human intervention, the demands of governed infrastructure become even more acute. Training will largely sit with specialized providers, but inference, particularly context-aware inference on regulated data is where production enterprise AI lives. That is the workload we have built to operate. And as customers develop a clearer picture of their data residency requirements, more of those workloads will move into governed Private Cloud, deployed across our global data center footprint in the jurisdictions and sovereignty zones our customers require. That is why we are doubling down on VCF 9 and Broadcom this year.

Our full year Private Cloud growth outlook remains on track. We have signed engagements with AdventHealth, Seattle Children's and a strategic Database-as-a-Service partner onboarding through the rest of the year. We are also seeing encouraging pipeline momentum on our Palantir and Uniphore partnerships where context-aware inference and government agent workflows are gaining traction at deal sizes that we have not historically seen. The AMD partnership announced today adds a further layer of future optionality as governed AI compute becomes more central to how regulated enterprises operate. Together, these give us confidence in the full year Private Cloud growth profile we are reaffirming today.

Now for our Public Cloud update. First quarter Public Cloud revenue was $443 million. Services revenue grew 10%, reflecting our continued shift towards higher-value engagements. Our customer wins this quarter highlight the breadth of our platform capabilities and our deepening presence in the AI space. First, we are powering a large-scale enterprise-wide multi-cloud transformation for a leading health care technology organization. Through a governance model, we are delivering program managed migrations, modern architecture, intelligent automation and measurable cost optimization, ensuring each workload is placed on the right platform for the right reasons.

Second, Rackspace is serving as the implementation and managed services delivery engine for a high-growth AI-native database as a service partner operating across both Public and Private Cloud environments. Our execution capabilities are a direct accelerant to our partners' client acquisition and market expansion, reflecting a high-value compounding partnership driving differentiated multi-cloud Database-as-a-Service outcomes.

Our service portfolio is built for where enterprise AI is headed, production, not experimentation. We are embedding engineers directly into customer environments moving from strategy to live deployment in weeks with governance and accountability built in from day 1. New partnerships expand our ability to deploy context-aware inference, governed agent workflows and forward deployed engineers inside customer environments, giving enterprises a governed path from strategy to inference workloads in production. We are complementing this with purpose-built capabilities in AIOps, identity security and data resilience, addressing the operational and security demands that become nonnegotiable once AI moves into production environments.

In summary, Public Cloud is executing. As inference workloads move into production, we are increasingly positioned as the partner enterprises rely on to operate, secure and optimize their cloud environments with full accountability to match. The results this quarter confirm the thesis: governed AI infrastructure as the foundation, an integrated technology stack of curated partners running on top of it, one accountable operator responsible for the outcomes. That is what today's Rackspace delivers.

With that, I will turn it over to Mark for our financial results.

Thank you, Gajen. In the first quarter, total company GAAP revenue was $678 million, up 2% year-over-year, driven by solid Public Cloud performance. Non-GAAP gross profit margin was 18.3% of GAAP revenue, down 160 basis points year-over-year, reflecting the Private Cloud revenue timing dynamics we discussed. Non-GAAP operating profit was $31 million, up 20% year-over-year, driven by continued operating expense discipline. Non-GAAP loss per share was $0.06, flat year-over-year.

Cash flow from operations was $5 million and free cash flow was negative $9 million. We ended the quarter with $94 million in cash and $295 million in total liquidity, inclusive of the undrawn portion of our revolving credit facility. During the quarter, we repurchased approximately $96 million of debt, reflecting our continued commitment to disciplined capital allocation and active deleveraging. This reduces our interest burden and strengthens our overall capital structure. We are making deliberate progress on leverage reduction while continuing to invest in strategic growth.

Turning to our segment results. Private Cloud GAAP revenue for the first quarter was $235 million, down 6% year-over-year, reflecting the timing of large deal onboarding within our health care vertical, consistent with the dynamics we outlined last quarter. Non-GAAP gross margin was 36%, down 110 basis points year-over-year, driven by lower fixed cost absorption on reduced revenue. Non-GAAP segment operating margin was 24.7%, an improvement of 30 basis points year-over-year, reflecting continued operating expense discipline.

In our Public Cloud segment, GAAP revenue was $443 million, up 7% year-over-year with services revenue growing 10% year-over-year. Non-GAAP gross margin was 8.9%, down 60 basis points year-over-year, reflecting higher infrastructure costs. Non-GAAP segment operating margin was 4.7%, up 50 basis points year-over-year, driven by improved operating expense efficiency.

Now on to our guidance. We are reaffirming our full year 2026 guidance in its entirety. Revenue, EBITDA and cash flow outlook all remain unchanged. The Q1 Private Cloud timing we described is fully reflected in our annual plan and our confidence in the full year outlook is unchanged. We continue to win larger complex engagements that carry longer deployment cycles but deliver greater revenue visibility, higher lifetime value and more durable recurring revenue streams. As they come online throughout the year, we expect Private Cloud to reflect the growth profile we committed to for 2026.

With that, I'll turn it back over to Gajen.

The market is trending in line with our expectations. And this quarter, we delivered proof across every layer of that thesis. Regulated enterprises are making a deliberate decision about where their AI was, who operates it and who is accountable for outcomes. Health care is now a pillar. One of the top 5 Epic workloads in the world runs on Rackspace governed AI infrastructure. Epic Managed Services is proprietary Rackspace IP, decades in the making and increasingly the foundation our health care customers are choosing as AI moves into production.

Sovereign is validated. BT Sovereign Cloud runs on Rackspace governed AI infrastructure. SDAIA in Saudi Arabia places us inside one of the world's most advanced national AI programs. These are anchor commitments, not pilots. The technology stack is complete. And this quarter, we extended it further.

VMware Cloud Foundation 9 as the control plane running across private, public, edge and sovereign environments, Palantir for governed data and AI operations with our first joint deal closing and a growing pipeline. Uniphore, enabling agent-based workflows with context-aware inference, Rubrik for data resilience and AMD, where we are establishing a new category of governed enterprise AI infrastructure, delivering 4 integrated capabilities from silicon to outcomes, Enterprise AI cloud, Enterprise Inference Engine, inference as a Service and Bare Metal AMD Instinct, one integrated system with an investment-grade counterparty co-invested in our success and Rackspace accountable for how it performs end-to-end. We are the operator of the full enterprise AI technology stack, one accountable partner where enterprise AI goes to production. That is Rackspace.

Thank you to our customers, partners and every Racker. And with that, back to Sagar.

Thank you, Gajen. Let us begin the question-and-answer session. Please go ahead.

[Operator Instructions] Our first question comes from Kevin McVeigh with UBS.

Let me start just congratulating you folks because obviously, there's been a lot of work to be done to get you folks to this level and a lot of patience and just that needs to be recognized. And I think I just wanted to kind of highlight that because there's a lot that's going into the results that are here today. I guess -- and there was an incredible amount of detail again, but maybe talk to how AMD dovetails into Palantir? And what else -- it sounds like the MOU is pretty far along. What else needs to be done to get it across the goal line? It sounds like it is, but is there anything in terms of what we should look for just as that officially gets signed? Or is it officially signed? Just again, it seems like it's pretty far along, but just if you could help us with that a little bit.

Kevin, thank you, and I appreciate your comments. Now look, I think when we look at this, I would sort of think about Palantir and AMD somewhat distinct from each other, just so that the -- starting with the Palantir relationship, that's really all about deploying and running customer workflows for the customer with forward deployed engineers, somewhat independent of what compute platform it runs on, right? Really think about compute more as what's the most efficient place to run that work any given workload.

And then having -- and then the AMD piece really fits into how -- first and foremost, it gives us CPU and GPU, which I think as we move further into inference and production workloads, being able to deliver that in an efficient manner allows us to now do it across sort of the CPU, GPU stack. And then in terms of the partnership itself, I think we are certainly well along the way there. I think we still need to get the financing locked down and sort of tightened up, but we feel pretty confident that we are on our way to getting that done and hopefully get it announced here in the near future. We feel pretty good about it.

That's super helpful. And then just again, if you could remind us the capacity in the Private Cloud versus the Public. And as these initiatives kind of scale, particularly AMD and Palantir, is that primarily across the Private Cloud as opposed to the public? Or just maybe help us understand that a little bit because obviously, there's a lot to digest and just a really, really nice outcome.

No. Great question, Kevin. This is sort of this market confusion. -- at least I think of it that way, right, because customer workloads are going to run across private and public depending on where that workload needs to land, right? And that's why sort of our VCF 9 partnership, the Broadcom VMware partnership gives us sort of think of it as a control plane across which we could somewhat elastically drive the workload, whether it be in Private or Public Cloud.

So capacity-wise, we have the partnerships on the public side, and now we have the partnership and hopefully here soon, the compute side up and running from a GPU perspective as well, which allows us then to really be somewhat agnostic with the customer really focus on what specific outcome they want and then how do we deliver that in the most efficient way for them across either a CPU or a GPU landscape, and that could be private or public, right? So like you said at the beginning, Kevin, that's like a ton of work that goes into sort of figuring all this stuff out.

And part of the challenge our customers have, right, is to think all of that stuff through, right, in terms of we're building a small language model or you're running on a large language model where do you run the inference, where do you -- how do you orchestrate that? How do you ensure that it's running as efficiently as possible, secure as possible, data residency is thought through, right? All of those. And our ambition is how do you take that complexity off the table for them and with our forward deployed engineers, really enable, support and accelerate their journey to become more AI-enabled or operate on a fully AI stack, right? So that's the opportunity we saw, and that's what we are truly -- and our customers are really guiding us through this. So pretty excited about it.

No, it's amazing. And then just one more. I don't want to be -- I want to be respectful for your time, but it sounds like any sense of how this starts to kind of fan in, it sounds like maybe in the back half of '26. And then is there any way to think about kind of just what type of margin this work would be coming in? I know it's probably relatively -- maybe a tougher question, but just any way to think about that? And then what potential capital needs you could have as you're standing some of this stuff up?

I think we are -- think of it this way, Kevin. We think of -- there are very -- there are 4 distinct capability sets, if you will, right, for that better way that we are bringing to market, right? It's governed Private Cloud on AMD silicon, right? Think of that as we own the entire outcome for our customer in partnership with our customer. So they don't think about anything that sits in between, right?

So yes, that would be -- if you think of it through the lens of margin, probably our most profitable business. Then there's context aware inference, which is really the next level of business where you're driving domain-specific data through inference and maintaining that domain data throughout the entire process. That's probably your next tier when you think about margin coming down, if you will, right? Then there is the inference layer, just purely, we are providing the tokens or the intelligence customers are using it through an API. And then lastly, sort of a lot of what the neoclouds do, which is the bare metal, right, which is probably a lower spend on the margin, right?

So yes, I think that as we ramp up, we will see our business sort of fluctuate across these 4 areas. Obviously, our intent is to end up with fully managed governed outcomes, but there's a journey to get there. And I think that's something we need to work our way through before we can give clear guidance around how that plays out.

Kevin, this is Mark. I would agree with that. I also think that it's going to be largely on par, if not accretive to existing gross margin rates across our Private Cloud business. And just in terms of timing, this is not something that we've got materially factored into our '26 guidance, right, just in terms of supply chain and delivery timing.

Our next question comes from David Paige with RBC Capital Markets.

Congrats on the great results here. I guess just at a higher level, it seems like Rackspace is moving in the right direction not only internally as a company, but where the industry is going in terms of CPU, GPU, running SLMs, LLMs, et cetera. So I'm just curious, you seem like you're the first -- you're the leader, but I guess, how is the competitive environment looking? And I guess as a follow-up, you mentioned the pipeline is strong. So should we expect more deals in the future? Or maybe just flush that out a little bit.

Sure. Good to meet you, David, and thank you for your comments as well. So yes, I think when I think about where we are, the -- how would I -- the orientation of the business right now is very much along the lines of helping customers really understand how they want to run AI workloads, right? Because if you think about where we sit today in our Private Cloud business, especially, a lot of the customer workloads that are regulated run on our environment. And so the ability for us to sort of guide them from there on to running AI-based workloads is sort of where we are seeing the most opportunity.

And when you look at the partnerships, right, either on the application stack, the Palantir Uniphore or on the compute stack, they just give us a much more integrated view of trying to tie all of this together or not trying but tying all of this together and delivering it.

So when you think of kind of your first question in terms of competitive environment, I haven't seen anyone yet that is able to put all of this together in one place and then own the outcome, right? I think that sort of makes a distinct difference, especially in a regulated or sovereign environment because I think that it becomes significantly unique.

To give you an example, just when I say governed in health care, it means HIPAA compliance, PHI security, clinical SLAs, that all of that has to be put onto the same platform and integrated and then delivered, right? So I don't -- I'm not -- I'm sure there will be competitors that show up, but having the consulting, the forward deployed engineers, the infrastructure, the compute and the partnership all stitch together, I hope it gives us a little bit of a lead and an edge in terms of where we sit. Sorry for the long answer, but I hope that makes sense.

No, that was very helpful. And I would agree. It does seem like you have that leadership position, which is great. So I guess -- yes, that's helpful. Yes. Maybe one more. There were some comments about the capital structure. It looks like it's getting into a better place. Just how should we think about the capital structure over the next like 12 to 24 months just evolving?

David, this is Mark. Look, our motivation or our intent is deleveraging, right? That's our top priority, right? So as we think about some of the deals we've announced, some of our capital requirements for this year, right, the intent is ultimately we've got our eye on 2028, the maturity, the debt stack that's going to be due in the middle of 2028 and getting deleveraged through increase in operating leverage, EBITDA as well as additional cash flow. So as we structure some of these deals, right, the intent isn't to go take on more expensive add to our existing debt maturities, but to structure things in a way that don't create further leverage, right?

We have decreased our operating leverage I think from 8.6 to 8.3 quarter-over-quarter, right? We continue to stay focused on the out quarters and finding ways to delever, right? You'll notice in the quarter, we actually repurchased some of our debt, roughly $96 million notional at a pretty significant discount, right? So we're looking for ways to deploy capital such that we can reduce that -- get ourselves to refinanceability over the next 12, 18 months.

That concludes today's question-and-answer session. I'd like to turn the call back to Sagar Hebbar for closing remarks.

Thank you, everyone, for joining us. If you have any questions, please e-mail us at [email protected]. Have a great rest of your day. Thanks, Liz.

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

Good day, and thank you for standing by. Welcome to the Rackspace Fourth Quarter 2025 Earnings Conference Call. [Operator Instructions] Please be advised that today's conference is being recorded. I would now like to hand the conference over to your speaker today, Sagar Hebbar, Head of Investor Relations. Please go ahead.

Thank you, and welcome to Rackspace Technologies Fourth Quarter 2025 Earnings Conference Call. I'm Sagar Hebbar, Head of Investor Relations. Joining me today are Gajen Kandiah, our Chief Executive Officer; and Mark Marino, our Chief Financial Officer. As a reminder, certain comments we make on this call will be forward-looking. These statements involve risks and uncertainties, which could cause actual results to differ. A discussion of these risks and uncertainties is included in our SEC filings. Rackspace Technology assumes no obligation to update the information presented on the call, except as required by law.

Our presentation includes certain non-GAAP financial measures and adjustments to these measures, which we believe provide useful information to our investors. In accordance with SEC rules, we have provided a reconciliation of these measures to their most directly comparable GAAP measures in the earnings press release and presentation, both of which are available on our Investor Relations website. I will now turn the call over to Gajen for an update on the business.

Thank you, Sagar. I want to start by framing clearly where we are going as a company and why. Since I joined 5 months ago, we have sharpened our strategy in response to a clear shift in the market. Organizations now expect AI to deliver returns on their investment. As a result, they are moving beyond isolated AI experiments to operating AI at scale inside core enterprise systems. AI is infusing every workload and as it becomes embedded in customer data, financial systems and regulated processes, where it runs starts to matter. Whether across edge, core, private cloud, public cloud or sovereign environments, those choices directly impact performance, cost and compliance.

Managing those environments as one coordinated system is critical, especially in regulated industries where lapses can cause service disruption, regulatory exposure and escalating costs. The market is also entering what many are calling a private cloud renaissance. As AI moves into data-sensitive and regulated workloads, enterprises are recognizing that not all of it belongs in a pure public cloud model. Demand for governed, private and hybrid architectures with greater control over performance, cost and data residency is accelerating.

Put simply, Rackspace is the infrastructure and operations backbone for enterprise AI, the layer that makes AI governable, scalable and real inside the environments that matter most. These are the environments Rackspace knows inside out. For 25 years, we have operated the compute, security and operations layer across private cloud, public cloud and edge in regulated industries where governance, sovereignty and uptime are nonnegotiable. Executing on this requires the right leadership. Since joining, I have made changes to our executive team, bringing in leaders with deep operational and delivery expertise. This was intentional.

The opportunity in front of us is not primarily a strategy challenge. It is an execution challenge. I'm confident we now have the team to deliver it. But as AI increasingly operates inside live workflows, the opportunity extends beyond infrastructure. Enterprises do not want to stitch together hyperscalers, global system integrators, AI vendors and platform providers. That model is fragmented and complex with responsibility spread across too many parties. What they want is a platform engineering partner, one that deploys engineers directly into the environment, works on the platforms where AI actually runs and stays accountable from the initial use case definition all the way through to production operations on governed infrastructure, not just uptime and outcomes.

Our partnerships are central to this model, and they reflect a deliberate shift in how we think about delivery. Rather than building a traditional services organization, we are building a platform engineering capability. In practice, that means we put our engineers directly inside the customer environment, getting AI into production alongside them, and then we run it for them day-to-day. Our forward-deployed engineers work directly inside customer environments on platforms like Palantir's Foundry and AIP, helping enterprises shape their AI road map, prioritize highest value use cases and then deploy and run those workloads on governed infrastructure.

As a strategic partner to Palantir, that includes data readiness, hosting and ongoing managed operations. We have 30 Palantir-trained platform engineers today and plan to scale to over 250 in the next 12 months. The early pipeline activity reinforces the model. We have a strong and rapidly growing joint pipeline of Palantir-related opportunities, initial AIP boot camps in progress and a growing number of data migration opportunities in flight. And we are excited about what that means for our partnership and for the customers we serve together.

Looking ahead to 2026, we see AI emerging as an important growth vector, not as a stand-alone product and not as a traditional services practice. As mentioned earlier, we are building a platform engineering model, forward-deployed engineers fluent in the platforms where enterprise AI actually runs, helping customers move from complexity to outcomes. At the center of that model is our private cloud infrastructure, the governed sovereign foundation purpose-built for regulated data-sensitive workloads. Our public cloud capabilities extend that reach across hybrid and multi-cloud environments, giving customers a consistent operating model wherever their workloads run.

Together, they form the platform on which our ecosystem is built. The ecosystem is constructed through a curated set of anchor partnerships. VMware powers the control plane, unifying compute, storage, networking and security with native AI workload support and sovereign data residency controls built in. Rubrik anchors the cyber resilience layer, enabling rapid threat detection, data protection and workload recovery through Rackspace Cyber Recovery Cloud, nonnegotiable in the regulated environments we serve.

Palantir brings the data and AI platform layer where use cases are defined, prioritized and deployed in production by our forward-deployed engineers. These are our anchor partners today, and we will add to this ecosystem deliberately as the modern AI stack continues to evolve. We meet our customers where they are. Through a modular approach, customers can leverage their existing investments and adopt what they need without ripping and replacing what is already working. This creates a self-reinforcing model. A stronger ecosystem drives deeper engagement. Deeper engagement drives incremental infrastructure demand across both private and public cloud, and reliable operations build the trust that extends relationships over time.

Rackspace is the infrastructure and operations backbone for enterprise AI, and we are building the ecosystem around that foundation so our customers can focus on what matters most, outcomes. The foundation is already shaping our financial trajectory. Our 2026 outlook reflects the inflection point taking hold. We expect private cloud revenue to grow 6% at the midpoint year-over-year, the first sustained growth in many years, anchored by large multiyear enterprise engagements. For public cloud, we expect revenue decline to approximately 6% year-over-year at the midpoint, primarily due to the planned transition of a large government contract as we exit lower-margin work.

Excluding the contract, public cloud services revenue will grow in the mid- to high teens. This growth reflects continued expansion in high-margin managed offerings even as we proactively reduce exposure to lower-margin infrastructure resale engagements. As we pivot towards larger multiyear enterprise engagements and layer in scaling AI services, quarterly revenue timing will increasingly be influenced by migration milestones and deployment schedules. As a result, beginning in 2026, we will move to an annual guidance framework. We believe emphasizing full year growth, margin expansion and execution provides a clear measure of progress than quarter-to-quarter variability driven by implementation timing.

We will continue to provide quarterly color on key drivers, including segment trends, margin trajectory and major ramps such as health care deployment moving into Q2 to ensure investors maintain full visibility into the underlying momentum.

Now turning over to our fourth quarter and full year results. We exceeded guidance across most metrics for the quarter. At a segment level, however, private cloud revenue was below our guided range due to a recently signed health care contract ramping more slowly than initially expected. Note, this was offset by outperformance in public cloud across both infrastructure and services. Operating profit for the company remained strong at $41 million and adjusted EBITDA came in at $81 million. For the full year, we delivered stable performance, improved bookings quality and continued progress towards a more platform-led durable growth profile. I'm pleased with our overall execution in fiscal 2025, highlighted by continued revenue stabilization in private cloud and growth in public cloud services.

With that, let me turn to segment performance, beginning with private cloud. Private cloud continues to serve as a foundational profit engine for Rackspace. In the fourth quarter, revenue came in at $241 million, below our guided range due to a newly closed health care deal ramping more slowly than initially expected. The deal is fully executed and is expected to begin ramping in the second quarter of 2026, reflecting additional client governance and oversight given its size and complexity. For the full year, private cloud revenue totaled $990 million, down 6% year-over-year compared to prior years of double-digit decline.

Early pipeline activity remains encouraging with double-digit opportunities currently in flight and initial use cases typically representing 7-figure engagements. Importantly, each use case serves as a tip of the spear. Our platform engineers work with customers to define the right starting point, scoped, high value and achievable, and from there, each deployment drives incremental infrastructure consumption across private, public or hybrid environments.

The engineering relationship and the infrastructure relationship grow together. During the quarter, we closed several high-quality private cloud deals that reinforce our strength in regulated data-intensive environments such as financial services and health care. One notable engagement in Q4 was a multiyear agreement with a top European retail and commercial bank. Rackspace is managing transformational migration, software-defined data center capabilities and managed services with a clear path to expand into cyber recovery, public cloud, AI and digital banking opportunities over time.

In addition, we secured multiple transformation-focused wins across infrastructure and platform modernization. These included winning a mission-critical workload for a global online trading and financial services platform by modernizing hundreds of bare-metal servers into a virtualized software-defined infrastructure environment, improving resilience, scalability and operational efficiency while mitigating churn risk. We also entered into a new agreement with a fast-growing AI-enabled digital platform to host and manage its next-generation human-in-the-loop architecture designed to scale intelligent real-time engagement across a large user base. These wins share a common theme.

Customers are choosing Rackspace to modernize and operate mission-critical workloads where reliability, security and compliance are nonnegotiable and where application-led services drive long-term strategic value. From a product perspective, private cloud continued to expand its platform capabilities. We introduced support for the latest release of Oracle PeopleTools, enhancing usability, embedded analytics and life cycle management for enterprise ERP environments. These improvements help customers drive higher productivity, stronger system governance and better decision-making in complex business systems.

We also launched RackConnect Global Internet on Partner Fabric, extending Rackspace's network edge to partner ecosystems. This offering provides high-performance, resilient Internet connectivity with predictable costs and enterprise-grade routing, enabling customers to deploy and manage modern, hybrid and sovereign cloud architectures with confidence. Private cloud remained central to our strategy in 2025 with sustained customer engagement and steady execution across key programs. While these engagements typically carry longer deployment cycles, they provide greater revenue visibility, higher lifetime value and more durable recurring revenue streams.

As we move through 2026, our focus is on accelerating our growth vectors as customers migrate into their future state environments. As these programs mature, we expect improved revenue predictability and expanding operating leverage over time. Now turning to public cloud. In the fourth quarter, revenue totaled $442 million, exceeding our guided range. This performance was driven by strength across both services and infrastructure resale. Services revenue grew 28% year-over-year, reflecting continued momentum in higher-value engagements.

For the full year, public cloud revenue reached $1.7 billion, with services revenue growing 6%. These results reflect continued progress in executing our services-led strategy centered on operating, securing and modernizing complex cloud environments. Our increasing focus on enterprise customers reduces exposure to long-tail churn and positions us with larger enterprise-grade transformation engagements where we see stronger retention, deeper wallet share and more durable revenue streams. During the quarter, we secured a broad set of public cloud wins that reinforce Rackspace's role as a trusted partner for running large-scale customer-facing platforms.

In the Americas, we helped a major digital media and advertising consumer-facing company transform its AI-powered services, serving hundreds of millions of users by building production-grade framework that speeds deployment of machine learning models and ensures reliability and governance. We also advanced AI solutions for a global aviation services provider, enabling real-time access to operational data, improving response times and driving measurable efficiency gains across regulated environments.

In EMEA, we were selected as a strategic cloud managed services partner for a leading European bank, providing round-the-clock monitoring, security and optimization for core banking systems. For one of the largest diversified businesses in the Middle East across multiple industries, we are partnering on a comprehensive enterprise data platform modernization program that provides visibility across their diverse investment portfolio, enabling faster time to insight for better investment decisions. These wins highlight Rackspace's unique strength in regulated and data-intensive industries and our ability to deploy AI solutions at scale while ensuring reliability, compliance and operational excellence.

We also continue to expand our public cloud product portfolio in Q4 with offerings designed to simplify adoption and accelerate time to value. We launched Rackspace Managed Cloud Database Operations, providing fully managed, secure and compliant database services across hyperscale environments. We also introduced streamlined deployment options for enterprise software and AI-enabled managed services. Together, these enhancements help customers adopt, scale and manage cloud and AI services more effectively as their environments grow.

Across public cloud, AI is moving from experimentation to production. Customers increasingly rely on Rackspace to operationalize AI with governance, security and managed services, areas where execution, trust and reliability matter most. Our partnership with Palantir is a proof point of the platform engineering model in action. Forward-deployed engineers embedded with customers working on foundry and AIP shaping use cases building towards production. This is how enterprises deploy AI into live workflows in weeks rather than months, with governance built in from day 1.

It is not managed services in the traditional sense. It is a new delivery architecture. That means engineers embedded in the customer environment, AI in production in weeks and Rackspace running it reliably from day 1. In summary, 2025 marked a year of meaningful structural improvement for our public cloud business. We drove stronger customer retention, executed targeted operational initiatives that supported margin expansion and delivered solid performance across the portfolio.

As we enter 2026, we see AI evolving into a tangible growth driver with encouraging pipeline conversion trends and measurable delivery efficiency gains. Our focus remains on higher-value managed services, including AIOps, site reliability engineering, governance, modernization and cost optimization. As AI workloads expand, customers increasingly need support orchestrating across edge, core and cloud environments while balancing accelerated compute demand with governance and cost discipline.

Rackspace enters 2026 with a clear identity and the team to execute on it. The work of the last 5 months has not just been about strategy. It has been about building the right leadership, sharpening our focus and making deliberate choices about where we compete and how we win. Those choices are now made and the team to deliver them is in place. The market is moving in our direction. Enterprises are realizing that operationalizing AI at scale inside regulated data-sensitive environments requires more than technology.

It requires a partner with deep infrastructure expertise, governance discipline and operational accountability, a partner who can help them shape the journey, not just run the infrastructure underneath it. That is Rackspace. We are building a platform-engineering model, forward-deployed engineers embedded in the customer environments, working on the platforms where enterprise AI actually runs, helping customers define where to start, how to scale and how to operate with confidence. That capability sits on a foundation that took 25 years to build, governed private cloud infrastructure operating across regulated industries where uptime and sovereignty are nonnegotiable.

Platform engineering, forward-deployed execution and governed infrastructure in one accountable relationship. We don't advise on the journey. We build it and run it. That is what makes Rackspace different. That is the layer that makes enterprise AI governable, scalable and real. We will execute with precision, earn trust at every step and deliver durable growth. I'm confident in this team, this model and this moment for our company. With that, I will turn it over to Mark for our financial results and outlook.

Thanks, Gajen. Three things stand out in the quarter. First, we beat revenue guidance, driven by public cloud outperformance. Second, non-GAAP operating profit came in at $41 million, above the high end of our range with margins up 120 basis points sequentially. Third, we ended the year with $397 million in total liquidity and $60 million in cash flow from operations for the quarter, a strong foundation heading into 2026. In the fourth quarter, total company GAAP revenue was $683 million, non-GAAP gross profit margin was 18.1% of GAAP revenue, down 180 basis points sequentially, driven by lower revenue in private cloud and higher mix of public cloud infrastructure.

For the full year 2025, non-GAAP gross profit margin was 19.4%, down 120 basis points year-over-year. This was, again, a result of a year-over-year decline in private cloud revenue. Non-GAAP operating profit was $41 million, while non-GAAP operating profit margin was 6% of GAAP revenue, an increase of 120 basis points sequentially. For the full year 2025, non-GAAP operating profit margin was 4.7%, up 80 basis points versus prior year, driven by lower OpEx as we continue to optimize costs across the company. Non-GAAP loss per share was $0.01, beating our guided range of a $0.03 to $0.05 loss per share. Cash flow from operations was $60 million and free cash flow was $56 million in the fourth quarter.

For the full year, cash flow from operations was $151 million and free cash flow was $91 million. We ended the year with $106 million in cash on hand and $397 million in total liquidity.

Turning to our segment results. For the private cloud segment, GAAP revenue for the fourth quarter was $241 million, below our guided range due to a recently signed health care contract ramping more slowly than initially expected. private cloud non-GAAP gross margin was 35.7%, down 240 basis points sequentially due to lower revenue and less fixed cost absorption. Non-GAAP segment operating margin at 26.1% was down 80 basis points sequentially. In our public cloud segment, GAAP revenue was $442 million, above our guided range, primarily driven by both cloud infrastructure volumes and services revenue.

Non-GAAP gross margin was 8.5%, down 70 basis points sequentially, driven by a higher mix of infrastructure revenue. Non-GAAP segment operating margin was 4.5%, up 120 basis points sequentially due to improved operational efficiencies. Turning to guidance. As Gajen mentioned, beginning in 2026, we are shifting to an annual guidance framework. Quarter-to-quarter results are increasingly influenced by the timing of large deals, making short-term forecast less predictive of our long-term trajectory.

Focusing on annual guidance aligns our external communication with how we run the business, prioritizing full year growth, margin expansion and operational execution over short-term variability. While we are moving to an annual guidance framework, we are committed to providing regular substantive updates on the drivers behind the numbers each quarter. We expect full year GAAP revenue to be $2.6 billion to $2.7 billion, down 1% year-over-year at the midpoint. From a segment perspective, we expect private cloud revenue of $1.25 billion to $1.75 billion, up 6% year-over-year at the midpoint and public cloud revenue of $1.575 billion to $1.625 billion, down 6% year-over-year at the midpoint.

In private cloud, we expect growth to be balanced across the year as large health care and other regulated deployments move into production. The revenue cadence reflects migration complexity and implementation timing, not demand softness. In public cloud, we expect services revenue to grow mid- to high teens year-over-year, excluding the planned transition of a low-margin large-government contract, reflecting continued momentum in higher-margin managed offerings.

Total non-GAAP operating profit is expected to be $160 million to $170 million, representing growth of 31% at the midpoint, driven by higher revenue and strong cost management. Adjusted EBITDA is expected to be $305 million to $315 million, up 12% at the midpoint, and non-GAAP loss is expected to be from $0.15 to $0.20 per share. Our non-GAAP tax rate is expected to be 26%, while non-GAAP other expenses will be in the $220 million to $230 million range. Non-GAAP share count is expected to be between 250 million and 260 million shares. Free cash flow is expected to be between $90 million and $110 million. With that, I will now turn it back over to Gajen for final remarks.

Before I wrap up, thank you to our customers, partners and all Rackers. In my first full quarter here, I have seen a company built on trust with our people, customers and partners. Our strengths are clear, a culture focused on customer outcomes, a portfolio designed for regulated environments and significant growth potential in health care, sovereign and AI.

As AI and complex workloads move into production, our role is to help clients orchestrate critical systems across private, public, edge and sovereign clouds, turning data into outcomes with reliability, security and precision. That is how we earn and keep trust. With that, I will turn the call back over to Sagar.

Thank you, everyone, for joining us. If you have any questions, please e-mail us at [email protected]. We look forward to engaging with the sell-side and investor community in the coming weeks as we continue to articulate our strategic road map and financial priorities. Have a great rest of your day.

This concludes today's conference. Thank you for your participation. You may now disconnect.

Good day, and welcome to the Rackspace Q3 2025 Earnings Call and Webcast. [Operator Instructions] Please note that today's event is being recorded. I would now like to turn the conference over to Sagar Hebbar, Head of Investor Relations. Please go ahead.

Thank you, and welcome to Rackspace Technology's Third Quarter 2025 Earnings Conference Call. I'm Sagar Hebbar, Head of Investor Relations. Joining me today are Gajen Kandiah, our Chief Executive Officer; and Mark Marino, our Chief Financial Officer. As a reminder, certain comments we make on this call will be forward-looking. These statements involve risks and uncertainties, which could cause actual results to differ. A discussion of these risks and uncertainties is included in our SEC filings.

Rackspace Technology assumes no obligation to update the information presented on the call, except as required by law. Our presentation includes certain non-GAAP financial measures and adjustments to these measures, which we believe provide useful information to our investors. In accordance with SEC rules, we have provided a reconciliation of these measures to their most directly comparable GAAP measures in the earnings press release and presentation, both of which are available on our Investor Relations website.

I will now turn the call over to Gajen for an update on the business.

Thank you, Sagar, and good morning.

I spent the first couple of months figuring out what we have, a terrific company centered on trust, both with each other as Rackers as well as with our customers and partners. And I will be devoting the next few months to accelerating growth, including how to best leverage advances in AI to capture external opportunities and to improve internal efficiencies.

Reflecting on my initial weeks at the company, 3 strengths stand out. First, a Racker culture that blends deep engineering with an obsession for customer outcomes. Second, a portfolio built for regulated environments where reliability, security and compliance are nonnegotiable. And third, significant growth potential in at least 3 markets, 2 verticals in health care and sovereign, the other horizontal in AI, where our capabilities match real demand. In sum, we do not try to be everything to everyone. We aim to be the partner of record when it matters.

The enterprise market is shifting from pilots to production in AI, and it is growing more complex as data sovereignty and security requirements tighten. In this dynamic complex space, our role is clear. To help our clients orchestrate critical workloads across private cloud, public cloud, edge and sovereign environments. We turn data into outcomes through our advisory, security and managed services. We will build on our strengths. We will focus where we win, and we will execute with precision to deliver stronger reliability, greater predictability and enhanced security for our customers. This is how we earn and keep trust.

Now getting back to commentary on our quarter. Results for the third quarter met or beat our expectations across all key metrics. Revenue, operating profit and EPS met or exceeded the midpoint of our guided range. Sales momentum remains strong with bookings as measured by annual contract value growing 5% year-over-year. The growth was primarily driven by private cloud, which secured several key wins.

Now let's get into our segment performance, starting with Private Cloud. Private Cloud continued to win several large long-term enterprise deals. Revenue came in at $250 million, meeting our guidance midpoint and down 3% year-over-year. Revenue continues to stabilize as prior period bookings ramp, reflecting business strength and consistent execution. Our focus on retention and bookings momentum is driving a solid path to long-term growth. We are expanding relationships with enterprise and sovereign customers, positioning Rackspace to capture new opportunities and drive future scale.

In Q3, we signed a leading global telecommunications provider to enhance the experience for more than 30 enterprise clients worldwide. This engagement centered on Rackspace Private Cloud and professional services, created a software-defined data center environment built for agility, scalability and consistency on a global scale. Beyond measurable value, it deepened our partnership and reinforced Rackspace as a trusted extension of our customers' service delivery model.

Another major win this quarter comes from a sovereign government customer focused on data and AI. Rackspace will manage a secure cloud environment, enabling multiple departments to host mission-critical applications safely and accelerate digital services for millions of citizens. These wins demonstrate the strength of our cloud capabilities and the trust customers place in Rackspace to deliver a secure, reliable solution at scale.

Private cloud also continued to deliver innovative solutions with 8 new releases in the third quarter. A key highlight was the launch of Rackspace Electronic Health Record Cloud Enterprise, a fully dedicated platform for mission-critical health care systems like Epic. It delivers leading availability, compliance and performance aligned with Epic honor roll standards and health care regulations such as HIPAA and HITRUST. It provides a strong foundation for health care organizations that need secure and compliant infrastructure for patient care.

We also introduced AI LaunchPad, a fully managed service that helps customers move from AI experimentation to production with GPU-powered environments, preconfigured AI tooling and expert support. AI LaunchPad helps enterprises scale AI with speed, security and cost transparency. Together, these launches show how Private Cloud continues to innovate across cloud, AI and security. We help customers modernize their most critical workloads with trust and speed.

Now turning to Public Cloud. In the third quarter, bookings grew 2% sequentially, led by the Americas. Revenues for the segment totaled $422 million, exceeding our guided range. Revenue increased 1% year-over-year and sequentially, driven by a 3% rise in services revenue, reflecting our disciplined focus on higher-value engagements. We are executing our strategy to expand our AI offerings and enterprise footprint, positioning Rackspace for growth ahead. In the third quarter, we signed a services engagement with a leading global e-commerce platform to provide site reliability engineering and AIOps services on their live streaming platform, improving performance and overall experience for the buyers and sellers.

We are also supporting a leading financial services institution that continues to invest in AI, cloud modernization and data analytics to enhance customer insight, automate decision-making and strengthen regulatory compliance. This customer partnered with Rackspace to develop an AI-driven governance platform that automates risk and compliance workflows, reducing approval cycles from months to days. Additionally, we were selected to lead one of the most advanced AI-led modernization programs in financial services using our Agentic AI solution to autonomously transform legacy code into AWS native platforms, creating a repeatable blueprint for enterprise modernization.

In Q3, our product launches reinforced our services-first strategy and expanded our portfolio capabilities. We introduced solutions that industrialize AI agents, modernize contact centers and enable flexible cloud environments, helping businesses scale autonomous operations, transform legacy systems and migrate workloads efficiently. These innovations expand our addressable market and position Rackspace as a trusted strategic partner for enterprises navigating complex cloud, AI and digital transformation.

Rackspace has an exceptional foundation. With clarity, focus and discipline, we will unlock its full potential. We will build on our strengths, focus where we win and execute with precision to deliver stronger reliability, greater predictability and enhanced security for our customers.

With that, I will turn it over to Mark for financial results and guidance.

Thanks, Gajen. In the third quarter, total company GAAP revenue of $671 million was up 1% sequentially, but down 1% year-over-year, coming in above the midpoint of our guidance. Non-GAAP gross profit margin was 19.9% of GAAP revenue, up slightly on a sequential basis, but down 120 basis points year-over-year, driven by lower cost absorption in private cloud and slightly higher infrastructure resale costs in public cloud. For the quarter, non-GAAP operating profit was $32 million, meeting the high end of our guided range and up 17% sequentially due to cost efficiencies in Private Cloud and lower corporate expenses.

Non-GAAP loss per share was $0.05 at the midpoint of our guided range of a $0.04 to $0.06 loss per share. Third quarter cash flow from operations was $71 million and free cash flow was $43 million. We ended the quarter with $100 million in cash on hand and $386 million of total liquidity. Turning to our segment results. Private Cloud GAAP revenue for the third quarter was $250 million, meeting the midpoint of our guidance. Private Cloud revenue decreased 3% year-over-year, reflecting customer transitions off legacy platforms, partially offset by new bookings coming online.

Private Cloud non-GAAP gross margin was 38.1%, down 50 basis points year-over-year and up 130 basis points sequentially. Non-GAAP segment operating margin was 26.9%, down 180 basis points year-over-year, driven by lower volumes and modestly higher operating expenses. Non-GAAP segment operating margin was up 230 basis points sequentially, driven by improved cost management. For Public Cloud, GAAP revenue was $422 million, surpassing the high end of our guidance, up 1% year-over-year and 1% sequentially, driven by higher services revenue and increased volumes across infrastructure resale.

Non-GAAP gross margin was 9.2%, down 110 basis points year-over-year due to unfavorable product mix. Non-GAAP segment operating margin was 3.3%, down 40 basis points year-over-year due to unfavorable product mix, partially offset by lower operating expenses. Turning to guidance. We expect fourth quarter GAAP revenue of $664 million to $678 million, flat sequentially and down 2% year-over-year at the midpoint. In Private Cloud, we expect revenue of $244 million to $252 million, down 1% sequentially at the midpoint.

We expect Public Cloud revenue of $420 million to $426 million, flat sequentially at the midpoint. Total non-GAAP operating profit is expected to be $32 million to $34 million and non-GAAP loss per share is expected to be in the range of $0.03 to $0.05. Our non-GAAP tax rate is expected to be 26% and non-GAAP share count is expected to be between 242 million and 244 million shares.

I'll now turn it back over to Gajen for final remarks.

Before I wrap up, I want to say thank you to our customers, partners and all Rackers. Two months in, I am proud of how the team delivered this quarter and focused on what is next. Our ambition is clear. We will be the leading hybrid multi-cloud partner for regulated, sovereign and mission-critical workloads. We will be the partner of record when it matters.

Sagar, back to you.

Thank you, Gajen. Before we move to Q&A, I would note that we'll be participating in the UBS Global Technology and AI Conference in Arizona on December 3, consistent with last year. With that, we will now open the line for questions. Please limit yourself to one question and one follow-up. Please go ahead.

[Operator Instructions] And at this time, we are showing no questioners in the queue, and I would like to turn the call at this time back over to Sagar Hebbar for any closing remarks.

Thank you, everyone, for joining us. If we did not get your question or if you have a follow-up, please e-mail us at [email protected]. Have a great evening, everyone.

Thanks, Chris.

Thank you, and thank you for attending today's conference call and webcast. You may now disconnect your lines, and have a pleasant day.

Good day, and thank you for standing by. Welcome to the Rackspace Second Quarter 2025 Earnings Conference Call. [Operator Instructions] Please be advised that today's conference is being recorded. I'd now like to hand the conference over to Sagar Hebbar, Head of Investor Relations. Please go ahead.

Thank you, and welcome to Rackspace Technology's Second Quarter 2025 Earnings Conference Call. I'm Sagar Hebbar, Head of Investor Relations. Joining me on today's call are Amar Maletira, our Chief Executive Officer; and Mark Marino, our Chief Financial Officer.

As a reminder, certain comments we make on this call will be forward-looking. These statements involve risks and uncertainties, which could cause actual results to differ. A discussion of these risks and uncertainties is included in our SEC filings. Rackspace Technology assumes no obligation to update the information presented on the call, except as required by law.

Our presentation includes certain non-GAAP financial measures and adjustments to these measures, which we believe provide useful information to our investors. In accordance with SEC rules, we have provided a reconciliation of these measures to their most directly comparable GAAP measures in the earnings press release and presentation, both of which are available on our Investor Relations website. I will now turn the call over to Amar for an update on the business.

Thank you, Sagar, and welcome, everyone, to our second quarter 2025 earnings conference call. Results for the second quarter met our expectations across all key metrics. Revenue and operating profit exceeded the midpoint of our guided range, while EPS was within our guided range, marking our 12th consecutive quarter of meeting or exceeding guidance. Sales pipeline generation remains strong across both the business units with bookings, as measured by annual contract value, growing 2% sequentially and 16% year-over-year. The outperformance was primarily driven by Private Cloud, which secured several key wins. Non-GAAP operating profit grew 34% year-over-year, and we delivered positive cash from operations of $8 million for the quarter, reflecting our operational and financial discipline.

Now let me get into our segment performance, starting with Private Cloud. Private Cloud bookings in the second quarter of 2025 grew 24% sequentially and 42% year-over-year, driven by several large, long-term deals across key industries, including health care, BFSI and telecom. We also saw double-digit year-over-year bookings growth across both the Americas and EMEA, underscoring the broad-based strength of our go-to-market efforts. This solid bookings performance was despite a large health care deal that got pushed, and we expect this opportunity to close within the third quarter.

Revenue for the Private Cloud segment came in at $250 million, in line with guidance and down 4% year-over-year. We are seeing continued revenue stabilization as prior year bookings convert into revenue, reflecting the strength of our underlying business. Our disciplined focus on revenue retention and growing bookings momentum continues to lay a solid foundation for our long-term, sustainable growth.

We are also making strong progress in our strategic expansion into the mid-market and enterprise segments, positioning us to capture new opportunities and drive future scale. In April, we signed a long-term agreement with a leading health care provider in the U.S. to host their virtual desktop infrastructure supporting clinical kiosks. This was previously hosted on a hyperscale public cloud. The customer is getting enhanced control, consistent performance, predictable and highly competitive cost by transitioning the environment to Rackspace's secure Private Cloud. This win underscores Rackspace's expertise in delivering compliant, high-performance infrastructure for critical health care and other enterprise workloads.

We also expanded our relationship with a large U.K. bank through a strategic engagement to modernize its entire edge infrastructure. We have been engaged to deploy a secure network solution across approximately 80 branch locations. Our engagement is a comprehensive end-to-end managed service over 5 years.

Our Private Cloud team continues to deliver innovative solutions. In the second quarter, we had 13 product releases and 28 enhancements. More notably, we announced Rackspace OpenStack Business, a new open source dedicated solution for organizations running mission-critical or regulated workloads. This fully managed offering delivers enhanced performance, improved security and comprehensive operational support, all without the overhead and complexity of managing your own infrastructure.

Overall go-to-market and solutions momentum in the Private Cloud segment remains strong, reflected in both our results and customer wins. We remain focused on expanding our footprint while continuing to defend and grow our Private Cloud business.

Now turning to Public Cloud. In the second quarter, bookings for Public Cloud grew 1% year-over-year, primarily driven by strong performance in EMEA. Services bookings increased 6% sequentially, reflecting our disciplined focus on higher-value engagements. Revenue for the segment totaled $417 million, exceeding our guided range. Revenue declined 2% year-over-year due to expected declines in lower-margin infrastructure resale. We continue to focus on services revenue, which grew 3% sequentially and remained flat year-over-year.

We are also seeing success in increasing our footprint with existing relationships. In the second quarter, we expanded our engagement with a top-tier aircraft leasing company. They are leveraging Rackspace's data modernization and engineering services to accelerate their data transformation strategy and platform implementation. Additionally, we expanded our offering with a midsized cybersecurity company through a long-term deal that bundles infrastructure and services, demonstrating our continued ability to deliver integrated solutions that align with client needs.

On the product side, we introduced Rackspace CloudOps, a managed service that offers 24/7 operational support in the cloud. CloudOps is purpose-built for mid-market organizations at any stage of their cloud journey, helping them drive operational excellence, optimize performance and maximize cloud efficiency. This expands the service offerings that can be attached to infrastructure resale.

In summary, our focus on higher-value services, strategic bundling and expanding existing customer relationship is yielding positive results. Our services revenue continued to grow sequentially, underscoring continued progress in our Public Cloud business.

Turning to AI. We continue to make good progress with FAIR, which is Foundry for AI by Rackspace with over 80 wins and over 235 opportunities in our pipeline, of which over 20% are already in advanced stages, along with several active leads we are pursuing. Last month, we announced a strategic alliance with enterprise AI agent innovator, Sema4.ai, bringing together Rackspace's application and infrastructure management expertise with Sema4.ai's advanced 'SAFE' AI Agent Platform. Through this partnership, organizations will be able to rapidly deploy scalable, production-grade AI agents across key business functions built on a foundation of strong governance, transparency and security.

Additionally, we launched the Fair Model Context Protocol Enterprise Accelerator on the AWS Marketplace, empowering organizations to deploy AI agents at scale with robust security and seamless integration. This solution delivers 70% plus reduction in legacy application integration time, accelerating value realization and enabling real-world impact across health care, finance and manufacturing sectors.

We are also driving AI innovation across our service offerings in Public Cloud. AI integration within our services spans 3 areas: accelerating cloud migration time lines by 20% to 30%, reducing operational overhead for our managed services teams by 10% to 20% and automating security operations at scale. For example, we recently reduced migration time by 40% using SnowConvert AI for a leading health care services company. These AI at scale initiatives are accelerating time to value for customers and strengthening our position in enterprise transformation through intelligent automation.

Before I wrap up, I want to sincerely thank our customers, partners and all our actors. I'm pleased with what we have achieved this quarter and encouraged to see momentum in acquiring new and expanding with existing customers. We remain laser-focused on our key strategic priorities for 2025, building a sustainable business model that consistently delivers revenue, profit and cash flow growth. With that, I will turn it over to Mark to walk us through the financial results and guidance.

Thanks, Amar. In the second quarter, total company GAAP revenue of $666 million was down 3% year-over-year and slightly up sequentially, beating our guidance, driven by solid performance across both business units. Non-GAAP gross profit margin was 19.8% of GAAP revenue, slightly down year-over-year, driven by lower cost absorption in Private Cloud, while it remained flat sequentially. For the quarter, non-GAAP operating profit was $27 million, exceeding the high end of our guidance and up 34% year-over-year. The improvement was largely due to OpEx efficiencies in Public Cloud and in corporate overhead, partially offset by lower cost absorption in Private Cloud.

Non-GAAP loss per share was $0.06 at the lower end of our guided range of $0.04 to $0.06 loss per share. This was primarily due to higher expenses within the other income and expense line, driven by accruals related to data center leases as well as lower-than-expected diluted share count. Second quarter cash flow from operations was $8 million and free cash flow was negative $12 million. We ended the quarter with $104 million in cash on hand and $414 million of total liquidity.

Turning to our segment results. For Private Cloud, GAAP revenue for the second quarter was $250 million, which was in line with our guidance. Private Cloud revenue decreased 4% year-over-year due to customers rolling off older-generation offerings, partially offset by revenue from new bookings. Sequentially, Private Cloud revenue was relatively flat.

Private Cloud non-GAAP gross margin was 36.8%, down 50 basis points year-over-year and 30 basis points sequentially, primarily due to lower fixed cost absorption on lower revenue. Non-GAAP segment operating margin was 24.6%, a year-over-year decline of 190 basis points, driven by lower gross margins and higher OpEx. Sequentially, non-GAAP segment operating margin was up 20 basis points, driven by lower OpEx, partially offset by lower non-GAAP gross margin.

In our Public Cloud segment, GAAP revenue was $417 million, surpassing the high end of our guidance. Public Cloud revenue was down 2% year-over-year as a result of a decline in infrastructure volumes and flat sequentially, driven by growth in high-margin services business, offset by declines in low-margin infrastructure resale.

Non-GAAP gross margin was 9.6%, down 20 basis points year-over-year, reflecting onetime benefits realized last year. Sequentially, non-GAAP gross margin was up 10 basis points, driven by favorable rate and mix. Non-GAAP segment operating margin was 3.9%, up 140 basis points year-over-year due to improved OpEx efficiency and slightly down sequentially as a result of higher OpEx.

Now on to guidance. We expect third quarter GAAP revenue of $660 million to $674 million, flat sequentially and down 1% year-over-year at the midpoint. In Private Cloud, we expect revenue of $246 million to $254 million, flat sequentially and down 3% year-over-year at the midpoint. We expect Public Cloud revenue of $414 million to $420 million, flat sequentially at the midpoint. Total non-GAAP operating profit is expected to be $30 million to $32 million and non-GAAP loss per share is expected to be $0.04 to $0.06. Our non-GAAP tax rate is expected to be 26% and non-GAAP share count is expected to be 239 million to 241 million shares.

In the second half of 2025, we expect strong free cash flow generation, positioning us to exit the year with $70 million to $80 million in positive free cash flow. This trajectory reflects the strength of our business model and financial discipline. I will now turn the call back over to Sagar.

Thank you, Mark. Let us begin the question-and-answer session. [Operator Instructions] Please go ahead.

[Operator Instructions] Our first question will come from Kevin McVeigh with UBS.

Congratulations on the results. I don't know whether it's for Amar, but maybe both. Maybe talk about the guidance. It looks like a little bit of uptick sequentially, but definitely more outpaced success on the free cash flow. So maybe talk about -- is there any seasonality you think about in the guidance sequentially just relative to kind of where you came in? And then ultimately, if you could spend a minute on the free cash flow conversion as well.

Go ahead, Mark.

Yes, sure. So yes, thanks, Kevin, for the question. Yes, in terms of our Q3 guidance, you're right, overall $660 million to $674 million with the midpoint around $667 million, right? We're seeing things ultimately kind of flat sequentially from a Private Cloud perspective. We are forecasting some uptick on the Public Cloud side, especially on the services, while infra continues to stay sort of flattish to slightly down.

And in terms of free cash flow for the year, you saw we called out positive for the second half, positive for the full year. We did have some seasonality in the first half of the year related to some kind of onetime vendor prepayments, and those will not cycle in the second half. So that's driving a lot of our improvement as well as higher adjusted EBITDA and overall working capital performance. So I feel pretty confident about that free cash flow range.

And so Kevin, if I may just give some color on Private Cloud. So as Mark mentioned, we are forecasting a flat revenue in Private Cloud sequentially. Now this will be, Kevin, as you know, this is 3 quarters in a row. As we had mentioned before, we expect the Private Cloud business to start stabilizing, and that's exactly what we are seeing. And we feel good about the bookings performance that we had.

The mix of the bookings also came in quite favorable. It was a broad-based bookings performance in the Private Cloud business, and so pretty pleased with the performance there. In fact, just to give you some color here, the mix of the bookings in Private Cloud has actually changed significantly from a deal size perspective. Now if you go back to fiscal '22, roughly about 60% of the deals that we had were about small-sized deals, right, with lower ACV value. And now if you -- and about 40% was midsized to large-sized deals. And that has now actually flipped in 2024 and 2025. First half of '25, 40% of the deals were small deals and 60% was large and midsized deals. So that's the very important dynamics that we are starting to see, and this is on top of us growing a double-digit CAGR in the last 2.5 years.

Similarly, the contract length has also gone up. In fact, the contract length, if I have to just go back to '22, we had roughly 25% of our bookings in fiscal '22 where deals were longer than 24 months. Today, in first half of '25 as well as in fiscal '24, that number is now close to 50%. So the deal sizes have gone up. The contract length has gone up, which means we are really building a good book of business here across a lot of -- most of the verticals as well as from a geo perspective.

And on Public Cloud, because since you asked about the guidance, in Public Cloud, we feel good about the services performance. This quarter, we saw services revenue in Q2 was flat sequentially. We expect that to -- was actually up sequentially and flat year-on-year. We expect that to -- services revenue to start growing in the second half. In fact, in Q4 of 2025, our fourth quarter, we expect our services business in Public Cloud to grow anywhere from 10% to 20% year-on-year. So which will be a real good turn in the business in the Public Cloud business. So pretty pleased with the performance in the Public Cloud business, too.

And Amar, just remind me, and I know we talked about this a couple of times, but the services on the private side and I guess, what's driving the strength on the public side? And then just any thoughts on the services, I guess, more on the implementation work on the private? Just anything just around services on the private side as well? I know maybe if you have just any thoughts.

Yes, yes. Thank you very much. So let's start with the Public Cloud side, Kevin. Just as a recap, we have 3 types of services that we offer to our customers. On one hand is Professional Services. And then you have managed services on the other end of the spectrum, which is long-term contracts and very sticky. And then right in the middle is Elastic Engineering. And then we offer this across applications, platform as well as data. We are starting to see broad-based strength across all those 3 services, mainly Professional Services. As we go and drive more cloud migration work, we also drive work in AI as an example, which are mainly Professional Services kind of engagement.

We are starting to see our data business, for example, I've mentioned that before, our data business this quarter in Q2, I mean, in the second quarter, grew sequentially -- the bookings grew sequentially significantly. So we are starting to see strength in data, strength in applications, strength in platform support across Professional Services, Elastic Engineering and managed services in that quarter.

So -- and the attach of our services to infrastructure also went up. About -- when we do an infrastructure sale today, 70% -- we attach 70% of services to it. So for every dollar of infrastructure, we are attaching at least $0.70 of services to this infrastructure resale business. So the services attach motion is working well, good execution on the field. And also, it's -- and the offerings that we have is playing to where the market is heading. More and more work is on the transformational side. Digital transformation is led by cloud and AI, and that really plays to our strength in Public Cloud. So that's -- those are the factors, macro as well as our execution that gives us confidence that we are now turning the corner on services.

On the Private Cloud side, we offer managed Private Cloud for our customers. Clearly, health care, we really hit the sweet spot with health care, just strong even in Q2. When I look at just the health care vertical in the first half, it grew 60-plus percent year-on-year compared to first half of last year from a revenue perspective, so really, really good performance there. We have good deals in the funnel, and we also are starting to see traction. We had good traction in the telco sector with some very good deals signed.

And if I look at the services component, the main services component in Private Cloud, Kevin, is all managed services, very, very sticky business. Once we get this business, it stays with us for the next 3 to close to 7 years. And that's the -- the average contract length has also gone up significantly in that business. Hopefully, that's helpful.

Our next question comes from Frank Louthan with Raymond James.

Great. You mentioned getting some more traction in mid-market. Kind of what investments do you think you'll need to make there, either on the sales or the support side? And then with regard to the partnership with some of the AI agents, how did that come about? And when can we begin to see some of the benefits of that more broadly across the business?

Yes, yes, absolutely. Thanks, Frank. So in terms of -- so the focus has always been, Frank, in mid-market and enterprise, both -- in both Public Cloud as well as Private Cloud business. And we have made those investments in our fiscal -- end of fiscal '23 and fiscal '24, and now you're starting to see benefit of this. For example, in our Public Cloud business, we have grown in Public Cloud for several quarters in a row from a bookings perspective.

So not much of investment -- incremental investments needed now from a go-to-market perspective, Frank. We will be making investments on the edge. For example, our health care vertical has really kicked off very well. We went from being a small player in 2022 to being a really good -- being a very viable, credible player in the health care provider space with our Private Cloud offerings in '24 and '25. So not much of investment. Most of the investments will be -- even the CapEx investments will be success-based. So if you win a customer, then only we making investments in CapEx.

Now talking about AI, and we have started to see a lot of traction in AI in both the businesses. In fact, let me start with Private Cloud first. As you know, our offering in Private Cloud is we would -- our goal is to become a private AI infrastructure provider for our customers. So we think about workloads, and we will be focusing mainly on inferencing workloads. That inferencing workload, Frank, will either be run on public environment, Public Cloud, Private Cloud or at the edge. And we like our chances of winning in the private AI as well as at the edge, and we'll partner with the hyperscalers on the Public Cloud side.

As an example, for the first time, we won a private AI infrastructure deal with a health care organization in the U.S. that actually supports adults with development disabilities. Now they were facing some major -- there were some major pain points there in terms of care delivery, manual and time-consuming review of services notes, lack of automation. And so we basically put -- delivered an AI-powered solution, which was a combination of a private AI anywhere managed infrastructure with NVIDIA GPUs as well as our Elastic Engineering services, and we wrap that around with managed services. So this has resulted in 80% reduction in the manual review time. It has improved the care of delivery. So this is a good example of how we are now basically also catering to the customers' needs on having their private AI inferencing workload close to where the data is.

Similar -- on the Public Cloud side, we implemented really a very good AI -- agentic AI platform with J.Crew, and we went public with that. J.Crew, as you know, is a leading fashion retailer. They were really struggling with the effectiveness and efficiency of their customer, vendor and employee support organization. So we actually implemented 3 distinct AI agents: one for their IT department, one for their vendor management and the third was for customer service. And this was architected powered by Amazon's Bedrock as well as cloud SONic models. So great examples of how we are winning now in the AI space.

We also announced -- since you asked about agentic AI, I want to also highlight this. We announced a good partnership with a company called Sema4.ai., which is a very innovative company backed by Mayfield venture capital firm. And our Rackspace and Sema4.ai are highly complementary in what we bring to the table for our customers. For example, Sema4.ai will provide the agentic AI platform and Rackspace then brings in the delivery muscle, including the infrastructure. And so we are basically bringing a complete turnkey solution for, I would say, cutting-edge AI-based agentic platform at the enterprise grade, both from implementation, operations and governance and bringing technology and service solutions together. So we feel very good.

And then lastly, we are also internally becoming an AI company, Frank. There's a lot to talk about AI. Our CTO, Srini Koushik and his organization, working with all our functional leaders, have done a fantastic job in implementing agentic AI within the company to drive productivity of our functional personnel. Also, it's now we're bringing it to the CSM as well as the sales community.

That concludes today's question-and-answer session. I'd like to turn the call back to Sagar Hebbar for closing remarks.

Thank you, Liz. Thank you, everyone, for joining us today. If we did not get to your question or if you have a follow-up, please e-mail us at [email protected]. Have a great evening, everyone.

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