Gajen Kandiah
Analyst · RBC Capital Markets
Thank you, Mark. Good morning, everyone, and thank you for joining us. I will begin my remarks with a review of our third quarter and our outlook as we add new layers to our public and private cloud offerings and add new partners, customers and channels to broaden and deepen our enterprise AI capabilities. Our large existing operating footprint is a meaningful advantage in an environment challenged by access to facilities with power and cooling, and our customer and prospect base is engaging us earlier in their modernization planning as they see what we can provide. I will also highlight several new customer wins and how we are putting the business in place to drive higher margin and EBITDA as we move from commitments to deployments. Let me start with the quarter and our outlook. For the third quarter, total company revenue was $609 million, a 9% decrease versus last year. Adjusted EBITDA was $75 million, up 8.5% versus last year. We are maintaining our full-year profitability outlook with non-GAAP operating profit guidance of $125 million to $135 million and adjusted EBITDA guidance of $285 million to $295 million. For the full year, our forecast at the midpoint is for operating profit to be up 3% and adjusted EBITDA to be up 5%. We are also raising our full-year revenue outlook and tightening the expected range. We now expect revenue of $2.51 billion to $2.56 billion for the full year 2026, raising the midpoint by $35 million to $2.535 billion. At the midpoint, revenue is expected to be down 6% year-over-year. Current consumption is trending higher in public cloud, supporting an upward revision to our full-year revenue outlook. Our private cloud business remains stable. We are modestly adjusting our revenue forecast in private cloud to reflect the timing of a customer deployment shifting from Q4 into the first half of 2027 as well as capacity reservations for new customer opportunities as we expect to accelerate deployments under our AMD agreement. Importantly, we have made meaningful progress in contracting for both AMD and NVIDIA compute under long-term agreements. Pending finalization of financing and other deployment conditions, we now expect to be operating approximately 20 to 22 megawatts of cumulative high-performance compute for AI applications by the end of 2027, inclusive of the Together AI deployment announced earlier today. Once fully deployed, we expect these 20 to 22 megawatts of cumulative capacity to generate annualized run rate revenues between $420 million and $460 million with EBITDA margins of 60% plus, assuming deployment and utilization consistent with our current plans and expectations. As I enter my second year as CEO, we have moved from establishing a strategy and creating a framework to execute it to now beginning to translate our go-to-market efforts into commitments and deployments. Our goal is to establish Rackspace as the operator of the full enterprise AI stack with repeatable solutions for regulated environments bolstered by domain expertise built over years of experience operating across industry sectors and partnering with leading global systems integrators and software solution providers. For us, that means bringing together the infrastructure, compute, data and AI platforms and remaining accountable for the engineering and operating services we deliver. Our customers retain control of their data, models, technology choices and where their AI runs. We have been very deliberate about how we participate in this market. We are not building a business around speculative GPU capacity or pursuing growth simply for the sake of adding megawatts. We believe our existing facilities gives us an advantage in time to market, capital efficiency and execution risk compared with developing entirely new infrastructure. Existing infrastructure does not eliminate the need for investment, but it gives us an opportunity to direct that investment towards customer deployments rather than recreate every element of a new data center or requiring customers to move everything onto a single platform. Discipline remains central to our approach. We intend to weigh investment decisions against customer commitments, delivery readiness and financing and evaluate each deployment on its expected cash returns. Strengthening our balance sheet remains a priority. The opportunity in AI does not change that responsibility. It makes disciplined execution more important. Everything builds from our existing public and private cloud businesses with decades of experience operating mission-critical enterprise environments. The customers asking us to deploy inference capacity are, in most cases, customers whose applications, data and infrastructure we already operate. The AMD GPUs and CPUs are being deployed into our existing data centers that we operate, which have existing power and cooling infrastructure. The forward deployed engineers deploying Palantir are working inside many of these enterprise environments we already manage. This means we are extending an enterprise operating business, not starting a separate one, and new AI platforms are interested in Rackspace for this very reason. Customers are coming to us earlier and higher in the stack for modernization, data platforms and AI operating models before the managed services work begins. This morning, we announced a definitive agreement with Together AI for NVIDIA's GB300 infrastructure with an anticipated total contract value of $380 million over several years, subject to certain conditions. Under the contract, Rackspace will provide and operate the dedicated infrastructure, power, liquid cooling, networking and storage with the ability to add security, governance and compliance controls for end customers in regulated industries. We currently expect this to be in service by mid-2027. Separately, we also entered into a letter of intent with Together AI. It covers 2 things: potential future capacity expansion, which we believe could represent a potential multibillion-dollar long-term opportunity and a proposed joint go-to-market for enterprise AI solutions with Together AI providing inference and Rackspace providing the infrastructure platforms and forward deployed engineering. The LOI is not a definitive agreement and is subject to future agreements and other conditions, but we are excited about the opportunity to partner with Together AI and grow our relationship. We expect to share more details as this LOI evolves or converts into definitive agreements. I am pleased with our progress under the initial 30-megawatt strategic AI infrastructure agreement powered by AMD silicon. We continue to anticipate quarterly deployments of AMD capacity in steady quarterly tranches through 2028 and are pleased with our demand pipeline. We will begin 2027 with roughly 2 megawatts deployed. We are currently seeing potential opportunities to accelerate AMD deployments, including up to 5 megawatts in Q1 to reach approximately 7.5 megawatts cumulative by March. After that, we currently anticipate adding about 3 megawatts per quarter, reaching close to 11 megawatts at Q2, 14 megawatts at Q3 and approximately 17 megawatts by year-end. Note that these amounts refer to AMD deployments and exclude the Together AI deployment on NVIDIA GPUs announced earlier today. This forecast is approximate and actual timing could differ due to a variety of factors, including availability of financing, vendor delivery timing and data center readiness. We are currently deploying environments for a previously announced global systems integrator and expect to begin recognizing initial revenue towards the end of the fourth quarter. Today, we also announced a definitive agreement with an anticipated total contract value of $230 million with Blacksmith, a fast-growing AI-powered developer platform focused on accelerating software delivery and improving code reliability. Under the agreement, Rackspace will provide dedicated bare metal compute powered by AMD EPYC CPUs and storage with deployment expected to begin in early 2027. I want to highlight that for more than 2 decades, Rackspace has worked alongside global systems integrators to build and operate customized enterprise solutions. This experience gives us a distinct advantage as GSIs look to bring enterprise AI solutions to their customers. Our partners bring industry expertise and customer relationships, while Rackspace provides the infrastructure, engineering and ongoing operations required to bring those solutions into production and operate them at scale. We see our growing GSI pipeline as an important accelerator of our enterprise AI strategy, complementing our direct sales and strategic alliance channels. I also want to update you on our Palantir partnership, where we continue to progress from contracts to deployment and production. Since our last call, we have signed 7 contracts across industries with 5 in active deployment and 2 in production. These engagements are addressing meaningful business challenges. For example, we are helping a regional U.S. health care system use AI-powered workforce analytics to manage overtime, one of the highest controllable costs. The solution is designed to replace manual spreadsheet-driven analysis with real-time insights to help leadership identify cost drivers and evaluate operational changes. We are also working with a global specialty chemical company to modernize its finance and reporting processes through AI. The customer engaged Rackspace for our forward deployed engineering expertise, beginning with a focused boot camp to identify opportunities and establish a path towards production. Across industries, we are developing a repeatable approach, combining technology, engineering expertise and ongoing operations to move AI from proof of value into production. Supporting this progress, we have more than doubled our Palantir certifications since July, now exceeding 800 across the organization, strengthening our technical expertise and ability to deploy and operate AI solutions for our customers. As part of our growing partnership, Palantir is also now a Rackspace shareholder, owning approximately 2% of Rackspace's common stock. Our pod strategy is designed to make enterprise AI easier to deploy and operate at scale. These are repeatable, pre-engineered environments that bring together accelerated compute, AI platforms, governance and continuous operations, reducing the need to build each solution from scratch. At the foundation of this strategy is our enterprise sovereign pod, supported by NVIDIA, Dell and Palantir architecture, which combines dedicated AI infrastructure, data and model governance, operational controls and forward deployed engineering expertise to help enterprises deploy and operate AI in production while maintaining authority over their data, technology choices and AI environments. Building on this foundation, our Health Care Pod adds security and governance controls designed to support customers' compliance obligations, protect sensitive health care data and integrate with existing health care systems. The pods also enable our integrator partners to bring Rackspace capabilities to a broader enterprise customer base, and we expect to develop additional industry-specific pods for regulated sectors with our partners over the next year. The recent elections have brought new greenfield data center opposition to the fore of the markets. In addition, the markets have begun to ask questions about the timing risk and the capital required to build gigawatt scale data centers and its overall impact. We believe this makes Rackspace's existing data center capacity even more meaningful. Our existing data center provides capacity that we believe can be deployed efficiently without reliance on greenfield projects. Keeping these risks in mind, as we consider future deployment opportunities, we expect to evaluate each potential future project against 4 key criteria. First, infrastructure readiness. Can we leverage existing capacity, power and cooling to accelerate deployment? Second, customer commitment. Do we have a committed customer with the financial strength to support the investment? Third, capital structure. Can we structure the investment to optimize equipment financing, customer funding and Rackspace Capital? Fourth, what risks does Rackspace retain, construction, permitting, equipment, customer credit? And is that risk acceptable? Over 25 years of infrastructure deployment and operating experience position us to capitalize on these opportunities while maintaining the discipline necessary to deliver sustainable, profitable growth. To help support our growth initiatives, Rackspace recently entered into share purchase agreements with an investor group led by Voss Capital LP, providing for an aggregate $66 million investment in Rackspace common stock. We expect to use the net proceeds for general corporate purposes, working capital, capital expenditures and growth capital, including to fund GPU-related growth initiatives related to today's Together AI announcement. We appreciate the continued support of Voss and the additional investors as we execute on our strategic plan. Note that the hardware for the Together AI deployments, including NVIDIA GB300 NVL72 systems, is expected to be financed separately, and we are in active discussions with potential lenders. In summary, the strategy we previously articulated has begun to progress from commercial discussions to contracts and execution with financing structured deployment by deployment. In addition, we believe our existing infrastructure gives us a competitive advantage and our enterprise relationships, engineering capabilities and operating accountability give us the opportunity to create value beyond the infrastructure. Ultimately, our success will not be measured by how much capacity we announce. We believe it will be measured by how effectively we convert that capacity into contracted deployments, execute and deliver to those commitments and generate recurring revenue and sustainable return. With that, I'll turn it over to Mark to provide additional detail on our third quarter financial results as well as our near-term outlook.