DigitalOcean Holdings, Inc.

Thank you for standing by my name is jail, and I will be your conference operator today at this time, I would like to welcome everyone to the digital oceans first quarter 2026 earnings conference call. All lines have been placed on mute to prevent any background noise after the speakers remarks will be a question and answer session. If you would like to ask a question during this time simply press star one on your telephone keypad. If you would like to withdraw your questions you can press star one again, I would now like to turn the conference over to Radu Patricki head of investor relations, you may begin.

Great, thank you, Jael, and good morning, everyone. Thank you all for joining us today to review DigitalOcean's first quarter 2026 results. Joining me on the call today are Patty Srinivasan, our Chief Executive Officer, and Matt Steinfurt, our Chief Financial Officer. For those of you following along, an accompanying slide presentation is available on the webcast. Before we begin, let me remind you that certain statements made on the call today may be considered forward-looking statements. which reflects management's best judgment based on currently available information. Our actual results may differ materially from those projected in these forward-looking statements, including our financial outlook. I direct your attention to the risk factors contained in our filings with the SEZ, as well as those referenced in today's press release that is posted on our website. DigitalOcean expressly disclaims any obligation or undertaking to release publicly any updates or revisions to any forward-looking statements made today. Additionally, non-GAAP financial measures will be discussed on this conference call, and reconciliations to the most directly comparable GAAP financial measures can be found in today's earnings press release, as well as in our earnings presentation that outlines the discussion on today's call. A webcast of today's call is available in the IR section of our website. And with that, I'll turn it over to Patty.

Thank you, Radu. Good morning, everyone, and thank you for joining us today. We had an outstanding Q1 2026, and I'll start with four headlines. First, our momentum is accelerating. Q1 revenue was $258 million, up 22% year over year. with million-dollar-plus customers growing 179% year-over-year to 183 million in ARR. AI customer ARR grew 221% to 170 million, and we beat every financial target we shared in our last call. Number two, we launched the DigitalOcean AI Native Cloud last week, the most significant product launch in our history. with more than 15 new product launches across five fully integrated layers built into a modern, open, unified stack, purpose-built for the inferencing and agentic era. Third, we are investing to meet our growing customer demand and to seize the material opportunity in front of us. We raised $888 million in equity during Q1 to strengthen our balance sheet and quickly utilize that flexibility to secure 60 megawatts of incremental capacity that is slated to ramp throughout 2027, bringing our total committed capacity to 135 megawatts. And finally, we are again raising our near and medium-term guidance on the strength of customer demand and the incremental committed capacity. For 2026, we are increasing our full-year revenue growth projection from 21% to approximately 26% year over year and expect to exit Q4 approaching 30%. And this revised 2026 growth is entirely driven by our previously committed capacity without any top line benefit in 2026 from the new 60 megawatts. With the projected ramp of the incremental 60 megawatts in 2027, we are now projecting revenue growth of 50% or more in 2027. meaningfully higher than the 30 growth we communicated just last quarter i now spend a few minutes drilling down on each of these four headlines the momentum we are generating is clear evidence of both our differentiated position and our strong execution across the board it starts with the accelerating top line growth cuban revenue was 258 million up 22 year-over-year and up over 400 basis points over Q4 2025's already strong 18% exit growth rate. We are delivering this growth by continuing to delight our top cloud and AI native customers. Our AI customer ARR reached 170 million, growing 221% year over year. Our million dollar customer ARR reached 183 million, growing 179% year over year. These are not just customers experimenting on our platform. These are cloud and AI native companies scaling their businesses on DigitalOcean. Our rate of acceleration is also increasing. We delivered a record 62 million in incremental organic ARR, the highest in the company's history. Customers see our differentiated value and are leaning into our platform. RPO reached 243 million, up an extraordinary 1700% year over year. And we are doing all of this with strong profitability. We delivered 41% adjusted EBITDA margins and 18% trailing 12-month adjusted free cash flow margins. Drilling into our growth, our largest customers continue to be our fastest growing, and their growth continues to accelerate. ARR from our $100,000 customers grew 73%, while our $500,000 customers ARR grew 132%. ARR from our $1 million plus customers reached 183 million, growing at 179% year over year versus 123% last quarter. Our AI customers are the other key driver of accelerating growth. AI customer ARR reached 170 million, growing 221% year over year. And most critically, inference and core cloud pull-through increased to more than 80% of total AI customer ARR, up from 70% in Q4. That number tells you something important. We are not a GPU rental business. We are a full-stack cloud platform that AI-native companies depend on to build, run, and scale their production AI software. Last week at our deploy conference in San Francisco, we launched the DigitalOcean AI Native Cloud. And let me explain why this is a very significant step. Four forces are fundamentally reshaping AI right now. Inferencing has overtaken training as the dominant AI computing workload. Open source AI is now in production at over half of AI native companies. Reasoning models are driving the majority of token consumption and agentic systems are rapidly moving from experimentation to production. Together, these forces represents AI evolution from quote unquote thinking in which AI plays an advisory role to both thinking and doing in which AI delivers outcomes by executing autonomous tasks. The thinking part is powered by AI models and inferencing mode. And the doing part is delivered by a variety of modern cloud computing modules, all working together to take intelligent, autonomous, real-world action. DigitalOcean's AI Native Cloud is purpose-built for AI natives building exactly these types of workloads. It starts at the bottom with foundational layers. We operate a global scale infrastructure with 20 data centers purpose-built for AI workloads running a full stack core computing platform with a complete set of computing primitives that agentic workloads demand. Kubernetes, CPU and GPU droplets, advanced networking stack including virtual private cloud, object block and file storage, and high performance NFS. This is part of the doing layer. the foundation that vast majority of GPU-centric clouds simply don't have. Last week, we launched a new inference engine, which we co-invented with our customers to address their most critical inferencing needs, and it delivers a lot more than just serving tokens. It provides serverless and dedicated endpoints for serving up AI models, batch processing for asynchronous token generation, an intelligent policy-aware inference router that automatically selects the best model for cost and performance, a catalog of over 70 open source and closed source frontier models with day zero access, multimodal capabilities, and guardrails. For customers who want to run their own models, we support BYOM, or bring your own model. This is the quote unquote thinking layer, and it is far more than just serving tokens. It is about serving tokens efficiently with best in class performance, tightly integrated with other parts of the cloud. Augmenting this new inference engine is our data and learning layer for which we announced an enterprise version of our managed MySQL and Postgres databases for advanced workloads. We also announced new vector database support for building agentic workloads. We also launched a brand new managed agents platform to give AI natives everything they need to build, execute, and operate autonomous agents at scale with open harnesses, sandbox, state management, agent observability, toolbox for external integrations, and Plano-based orchestration on an open platform without getting boxed into a single LLM or platform provider. This is the DigitalOcean AI native cloud. Five fully integrated layers from silicon to agents with zero lock-in because we offer open source options at every single layer. This is absolutely essential as our target customers are AI native companies who are creating and monetizing software. AI infrastructure is a material cost of revenue line item for these AI natives, especially when they scale. Maintaining flexibility across models and platforms and leveraging the most efficient model capabilities for every specific task is an existential requirement for them. AI natives are increasingly adopting open source at every level, including multiple open source models, open agent harnesses, open source vector databases, and so on. To avoid lock-in and deliver compelling unit economics for their customers, as they go into hyper growth mode themselves. Building a truly open, fully integrated platform is hard, and that difficulty is precisely what makes our platform durable. The market is validating what we have long believed, that infrastructure without intelligence, without orchestration, and a full cloud platform is insufficient for what AI native workloads actually demand. Agentech applications require intelligence, CPU-based execution, stateful memory, manage high-performance storage and databases, and orchestration, all working together natively, not assembled after the fact. Our integrated stack is built for exactly this architecture, and that's what enables us to deliver differentiated performance with compelling unit economics that matter to our AI native customers. Leading independent benchmarking company, Artificial Analysis, recently reported that DigitalOcean delivers the number one output speed for leading open source models like DeepSeq version 3.2, QAN version 3.5, the 397 billion parameter model across all cloud providers. Our 230 output tokens per second on DeepSeq v3.2 is 3.9 times faster than one of the leading hyperscalers. This wasn't just a hardware story. It required co-designing every layer of the stack from NVIDIA's Blackwell Ultra GPUs to custom VLLM optimizations, including speculative decoding and kernel fusion, which is exactly the kind of deep engineering that differentiates the modern AI native platform from GPU forms and inference wrapper providers. The clearest validation of our strategy is the caliber of customers choosing to build and scale on us. We recently onboarded Cursor, one of the fastest growing AI applications ever built, for production inference, model fine tuning, and core cloud services. Ideogram, a leading text-to-image foundation model company, migrated production inference from a hyperscaler to our AI infrastructure running their own model rates at scale. And Hixfield AI, serving over 20 million creators with cinematic video generation, runs its full multi-model workflow on our integrator stack. Three different AI native companies in hypergrowth mode, running their production AI on our AI native cloud. And our pipeline continues to grow in both volume and strategic scale. Let me spend a couple of minutes on our competitive positioning with our new platform announcement. At a high level, unlike the hyperscalers, we are more open, purpose-built for modern software without the legacy complexity of enterprise workloads designed for the previous era. Compared to the GPU Neo clouds, which are optimized for large training clusters, we are a full-stack inferencing and agentic platform. And finally, while the inference wrapper providers offer tokens, we offer the breadth AI native builders need to build complete modern software without forcing them to stitch a platform together themselves. What makes our position genuinely durable is three compounding layers. Number one, our AI middleware. The Plano data plane and inference router built on technology from our recent Catanemo acquisition completed last quarter sits between the agents and the underlying infrastructure, intelligently steering workloads across models, regions, and accelerator types based on cost, latency, and availability tradeoffs at real time. Second, our managed agents platform extends computing primitives up the stack with secure runtimes, execution sandboxes, background workers, observability, orchestration, and much more. All purpose-built for agentic applications to be built and scaled on this platform. And the third is data gravity. Through managed databases, vector stores, caching, and object storage, production data lives inside our DigitalOcean AI native platform. Models and GPUs are not sticky. data is. For AI natives, the decision of where to build is rarely about a single feature. It is about platform breadth, quality of abstractions, openness of the platform, and the absence of friction. Delivering that requires deliberate, integrated engineering across every layer, from silicon to agents. It needs an AI native cloud which is what DigitalOcean has been building towards with millions of R&D hours over the last dozen plus years. The market opportunity is generational, and we are poised to earn more than our fair share. Global inference traffic will grow 10x by 2030, and agentic workloads consume 15 times more tokens than human users, a multiplier that compounds as AI matures. And we are already seeing it in our numbers. Our AI customer ARR is growing 221%, and over 80% of that is coming from inference services and core cloud, not bare metal. These are companies running full stack production AI on DigitalOcean, and they're accelerating. We are investing to meet this growing customer demand and to seize the opportunity in the massive inferencing and agenting markets. In Q1, we raised $888 million in equity. Proceeds that enable us to expand our data center and GPU capacity to meet our growing customer demand while strengthening our balance sheet. Matt will provide more details on the equity rates and our capital strategy later in our comments. But let me give you a brief highlight on our expansion plans. Starting with our existing committed capacity, we remain on track to deliver our previously communicated 31 megawatts as planned in 2026. with our Richmond facility beginning to ramp revenue in March. On top of this, we have now secured approximately 60 megawatts of incremental data center capacity across four locations, capacity that will ramp revenue throughout 2027. This brings our total committed data center capacity to approximately 135 megawatts. And given growing customer demand, We continue to actively pursue additional capacity beyond this new 60 megawatts, capacity that will be targeted to come online in 2027 and 2028. The opportunity in front of us is enormous, genuinely once in a generation. Every data point we see from our growing customer pipeline to the demand signals we are seeing and hearing from our largest customers, to the reactions and interest in our AI native cloud, reinforces that conviction. As we scale our business to meet this opportunity, we will continue to make the right long-term business decisions to seize this moment while building a durable and profitable growth engine. With momentum continuing to grow, we are further raising our near and medium-term outlooks. For the full year 2026, we now expect revenue growth of approximately 25% to 27% year-over-year. with an exit growth rate approaching 30%, a full year ahead of the guidance we provided just last quarter. This accelerated 2026 growth is based solely on the performance of our previously committed capacity and doesn't include any projected revenue uplift from the newly committed 60 megawatts. We expect to deliver this 2026 growth with high 30 suggested EBITDA margins and 9% to 12% adjusted free cash flow margins, which does include some startup costs for the new 60 megawatts. Looking further out, we now expect 2027 revenue growth of 50% or more, up from our 30% guidance last quarter, with approximately 40% adjusted EBITDA margins and high teen suggested free cash flow margins. This combination of rapid revenue growth and true durable profitability puts us in ratified company digital ocean is one of just a handful of names across a broad set of software and ai infrastructure players delivering both attractive gap operating margins and material revenue growth as i shared on our last call growth and discipline are not trade-offs for us they're both operating principles And our execution of these principles is clear in our results. With that, I will turn it over to Matt to walk through our Q1 results and our updated guidance in more detail. Matt, over to you.