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Good day and thank you for standing by. Welcome to the Rackspace's 1st quarter 2026 earnings webcast. At this time, all participants are in listen only mode. After the speakers presentation, there'll be a question and answer session. To ask a question during the session, you'll need to press star one one on your telephone. You will then hear an automated message advising your hand is raised. To withdraw your question, please press star one one again. Please be advised that today's conference is being recorded. I'd now like to hand the conference over to Sagar Hebbar, Head of Investors Relations. Please go ahead.

Thank you, and welcome to Rackspace Technology's 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, Rackspace Technology. 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 non-binding 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 three 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 healthcare, 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 am 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 healthcare, financial services, and sovereign environments where security, compliance, and accountability are non-negotiable. The MoU establishes AMD as the launch silicon across our four 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 Epic 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 skyrockets and operational risk increases. We solve this by integrating each vendor's IP, 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. 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 healthcare 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 non-negotiable, 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 healthcare, we signed a multi-year agreement with a major U.K. NHS Foundation Trust to migrate and operate workloads in a sovereign healthcare cloud with full outcome as a service and security embedded from the outset. 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 five Epic systems in the world. This quarter, we expanded our relationship to host and manage over 400 additional workloads on Rackspace Private Cloud. Healthcare 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 healthcare 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 1 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. 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 environments. 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 are built to operate.

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 governed 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. 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. We are powering a large scale, enterprise-wide multi-cloud transformation for a leading healthcare 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 Cloud 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 one. 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 non-negotiable 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, free cash flow was -$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 healthcare 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 runs, who operates it, and who is accountable for outcomes. Healthcare is now a pillar. One of the top five 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 healthcare 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. 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. With that, back to Sagar.

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

As a reminder, to ask a question, please press star one one on your telephone and wait for your name to be announced. To withdraw your question, please press star one one again. Our first question comes from Kevin McVeigh with UBS.

Great. Thanks so much. Good morning, 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, you know, just that needs to be recognized. 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, there was an incredible amount of detail, Gajen, but maybe talk to how AMD dovetails into Palantir and, you know, what else It sounds like the MoU is pretty far along. What else needs to be done just to I guess get it across the goal line?

Sounds like it is, but, you know, is there anything, you know, in terms of we should look for just as that officially gets signed, or is it officially signed? It just again, it seems like it's pretty far along, but just if you could help us with that a little bit.

Hey, Kevin, thank you, and appreciate your comments. Now look, I think when we look at this, you know, I would sort of think about Palantir and AMD somewhat distinct from each other, just so that Starting with the Palantir relationship, you know, 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.

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

We feel pretty good about it.

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

No, great question, Kevin. You know, this is sort of this marked confusion. At least I think of it that way, right? Customer workloads are gonna run across private and public, depending on where that workload needs to land, right? That's why sort of our VCF 9 partnership, the Broadcom-VMware partnership gives us sort of think of that, the control plane across which we could somewhat elastically drive the workload, whether it be in private or public cloud. Capacity-wise, you know, we have the partnerships on the public side, and now we have the partnership and, you know, 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? Like you said at the beginning, you know, Kevin, there's like a ton of work that goes into sort of figuring all of this stuff out. You know, part of the challenge our customers have, right, is to think all of that stuff through, right? In terms of, you know, we're building a Small Language Model or you're running on a Large Language Model. You know, where do you run the inference? Where do you know, 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. All of those. You know, and our ambition is, you know, how do you take that complexity off the table for them? With our forward deployed engineers really enable, support, and accelerate their journey to become, you know, more AI enabled or operate on a fully AI stack. That's the opportunity we saw, and that's what we are, you know, truly, you know, and our customers are really guiding us through this. We are pretty excited about it.

No, it's amazing. Just one more. I wanna be respectful of your time, but, you know, it sounds like, you know, any sense of how this starts to kind of fan in? It sounds like maybe the back half of 2026. Is there any way to think about kinda just what type of margin this work would be coming in at? 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?

You know, I think, you know, we are Think of it this way, Kevin. We think of There are very four distinct capability sets, if you will, right? For lack of a 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? You know, that would be, if you think of it through the lens of margin, probably our most profitable business.

You know, then there's context-aware inference, which is really the next level of, you know, business where you are 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? There is the inference there. Just purely we are providing the tokens or the intelligence customers are using it through an API. Lastly, sort of, you know, a lot of what the neo clouds do, which is the, you know, bare metal, right? Which is probably your lowest end on the margin, right? Yeah, I think that as we ramp up, we will see our business sort of fluctuate across these four areas. Obviously, our intent is to end up with, you know, fully managed governed outcomes.

There's a journey to get there, and I think that's something we need to work our way through before, you know, we can give, you know, clear guidance around how that plays out.

Yeah. Hey, Kevin, this is Mark. I would agree with that. I also think that, you know, it's going to be largely on par, if not accretive to existing gross margin rates across our private cloud business. Just in terms of timing, you know, this is not something that we've got materially factored into our 2026 guidance, right? Just in terms of supply chain and delivery timing.

Well, listen, it sounds like you're well on your way. Again, congratulations. Thank you.

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

Hi. Good morning. Thank you for taking my question, and congrats on the great results here. I guess just at a higher level, it seems like Rackspace is moving in the right direction. You're moving not only, you know, internally as a company, but where the industry is going in terms of, you know, CPU, GPU, running SLMs, LLMs, et cetera. I'm just curious, you know, you seem like you're the first, you know, you're the leader, but I guess, how's the competitive environment looking? I guess as a follow-up, you mentioned the pipeline is strong, so should we expect more deals in the future? Maybe just flush that out a little bit. Thank you.

Sure. good to meet you, David, and thank you for your comments as well. Now when I think about where we are, the orientation of the business right now is very much along the lines of helping customers really understand how, you know, how they want to run AI workloads, right? 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. You know, the ability for us to sort of guide them from there onto running AI-based workloads is sort of where we are seeing the most opportunity.

When you look at with 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. Not trying, but tying all of this together and delivering it. When you think of kind of your first question, in terms of competitive environment, I, you know, 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 you know, significantly unique.

To give you an example, just, you know, is like when I say governed in healthcare, it means HIPAA compliance, PHI security, clinical SLAs, right? All of that has to be put onto the same platform and integrated and then delivered, right? I'm not, you know 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 stitched 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 hope that makes sense, David.

No, that was very helpful. Thank you. I agree, it does seem like you have that leadership position, which is great. I guess, yeah. No, thank you. That's helpful.

Thank you.

Yeah, 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 12 to 24 months just evolving? Thank you.

Yeah.

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

We have decreased our operating, our operating leverage by I think from 8.6 to 8.3 quarter-over-quarter, right? We continue to stay focused on, you know, 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? We're looking for ways to deploy capital such that, you know, we can reduce that, get ourselves to refinance ability over the next probably 18 months.

Great. Thank you. That's very helpful. Congrats on the momentum and looking forward to working together.

Likewise. Thank you.

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 email 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. At this time, all participants are on a listen-only mode. 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. Welcome to Rackspace Technology's 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 non-negotiable. 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. 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're 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 roadmap, 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.

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 standalone 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. Non-negotiable 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, multi-year 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, multi-year enterprise engagements and layer in scaling AI services, quarterly revenue timing will increasingly be influenced by migration milestones and deployment schedules. 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 healthcare deployment moving into Q2, to ensure investors maintain full visibility into the underlying momentum. 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 revenues was below our guided range due to a recently signed healthcare 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 healthcare 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 seven-figure engagements. Importantly, each use case serves as a tip of the spear. Our platform engineering 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 healthcare. One notable engagement in Q4 was a multi-year 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. 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 design 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 non-negotiable, 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 lifecycle 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. 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 continued 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 one. 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 one. 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, 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 non-negotiable. 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-$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 healthcare 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 forecasts 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-$2.7 billion, down 1% year-over-year at the midpoint. From a segment perspective, we expect private cloud revenue of $1.025 billion-$1.075 billion, up 6% year-over-year at the midpoint, and public cloud revenue of $1.575 billion-$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 healthcare 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 and higher margin managed offerings. Total non-GAAP operating profit is expected to be $160 million-$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-$315 million, up 12% at the midpoint, and non-GAAP loss is expected to be from $0.15-$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-$230 million range.

Non-GAAP share count is expected to be between 250 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 healthcare, 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 email 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 roadmap and financial priorities. Have a great rest of your day.

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