DigitalOcean Holdings, Inc.

in an answer session. If you would like to ask a question during this time, simply press star followed by the number one on your telephone keypad. If you would like to withdraw your question, please press star one again. We ask that you limit your questions to one per person so we're able to get as many questions as possible. For operator assistance throughout the call, please press star zero. And finally, I would like to advise all participants that this call is being recorded. Thank you. I'd now like to welcome Melanie Straight, Head of Investor Relations to begin the conference. Melanie, over to you.

Thank you and good morning. Thank you all for joining us today to review DigitalOcean's first quarter 2025 financial results. Joining me on the call today are Patty Trini-Vaughan, our Chief Executive Officer, and Matt Steinforth, our Chief Financial Officer. Before we begin, let me remind you that certain statements made on the call today may be considered forward looking statements which reflect 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 SEC 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 the conference call and reconciliation to the most directly comparable GAAP financial measures can be found in today's earnings press release as well as in our investor presentation that outlines the financial discussion on today's call. A webcast of today's call is also available in the IR section of our website. And with that, I will turn the call over to Patty.

Thank you, Melanie. Good morning, everyone. And thank you for joining us today as we review our solid first quarter 2025 results. The top line growth momentum we generated in 2024 continued into Q1 and the results provide further evidence of our continued execution of our strategy. This strategy as outlined in slide four of our earnings presentation includes scaling with our digital native enterprise customers by helping them run large and complex workloads on our cloud platform and continuing to democratize the access of AI for both new generation AI native startups as well as for our existing 600,000 plus customers. I'm very pleased to share today the excellent progress we are making on both of these strategic priorities. My comments today will include a quick recap of our first quarter results, details on the progress we are making for our customers as we invest in product innovation and go to platforms. And a quick summary of the progress we are making on our financing strategy that Matt will detail later in the call. Let me start with the first quarter financial results and turning to slide five of our earnings deck. We had another solid quarter as revenue growth increased in the first quarter to 14% year over year to $211 million with our AI ARR continuing to grow north of 160% year over year. Q1 net dollar retention rate or NDR improved to 100% for the first time since Q2 of 2023 and we expect NDR to remain in a similar range as the last two quarters for the remainder of the year. In addition, we made further progress with our continued focus on our higher spending digital native enterprise customers, increasing revenue from customers who are at $100,000 plus annual run rate up to 41% year over year and to 23% of total revenue. This is well above market growth rates and was driven by a 27% year over year increase in customer count and 11% increase in their average spend with DigitalOcean. This improved growth was not confined to just this segment as our higher spend customers as a whole, which includes our builders, scalers and scalers plus customers grew to over 170,000 in number and their revenue grew 16% year over year making up 88% of our total revenue. The growth of these customers is a clear sign that our product innovation efforts and investments in strategic and targeted -to-market motions are helping digital native enterprises scale rapidly on our platform. While we continued investments and drove higher growth, we did so while delivering healthy profitability metrics including 61% gross margin and 41% EBITDA margins in Q1. Our 61% gross margins in Q1 is 200 bips higher than the prior year, an improvement that came from cost optimization that mitigated the near-term increase in cost of revenue that comes with the incremental capacity that we brought online in our new Atlanta data center. This new data center hosts multiple AI inferencing fabrics, some of which are already live for customers, powering real world customer inferencing workloads and is the first step in our long-term data center optimization strategy which includes both our cloud and AI workloads giving us a path to further gross margin optimization. Our 2025 capital program was heavily front-loaded in Q1 which drove the decline in quarterly adjusted free cash flow margin. While lumpy, this spent was contemplated in our full year 2025 plan and we remain on track for our full year free cash flow margin guidance. Having this new AI inferencing infrastructure in the new Atlanta data center enables us to go even faster on our AI initiatives helping us observe and learn from these customer workloads, ultimately enabling us to innovate faster in this rapidly evolving space. It also enables us to win even larger inferencing workloads like the $20 million plus multi-year inferencing commitment we closed with a strategic customer and partner early in Q2. With our focus now on large digital native enterprises, our push to win large workload migrations from other clouds and our funnel of larger AI native inferencing workloads, we are now seeing and winning larger and even multi-million dollar deals than we have in the past. While this is consistent with our strategy and we are now seeing the amounts of capacity to be available for the customer. To support these types of scale global workloads while maintaining our strong free cash flow generation, we are exploring additional funding strategies that Matt will explain in greater detail in his commentary that would increase our ability to more rapidly deploy new capacity to drive growth while minimizing the near term impact on free cash flow. Let me now give you some updates on product innovation that we are delivering for our digital native enterprise customers, starting with the enhancements to our core cloud computing platform outlined in page six of our earnings deck if you are following along. In Q1, we continued our target pace of innovation and released more than 50 new products and features, which is more than five times what we released in Q1 of the prior year. We accomplished this with No appreciable increase in R&D spend as a percentage of revenue, which is a testament to DO's engineering talent in our increasing use of AI for accelerating development and improving our operational posture. AI helped developers improving coding output by up to 40% and we also saw gains in our fleet help through AI based predictive maintenance. The new cloud capabilities we introduced in the quarter remain hyper focused on addressing the needs of our larger footprint customers to help them scale on the DigitalOcean platform. Let me highlight a few of those. We announced the GA of DigitalOcean Partner Network Connect, a secure high performance connectivity solution that simplifies multi cloud and hybrid cloud networking. This service enables our customers to establish private connections between DigitalOcean servers and other cloud providers or even on premise data centers. By bypassing the public internet, it enhances security, reduces latency and optimizes multi cloud and hybrid cloud networking. Our recent product updates over the last three quarters and enterprise grade availability are now attracting more complex workloads migrating from hyperscalers and this new capability of Partner Network Connect simplifies these by enabling a stage migration process by establishing secure connection between DigitalOcean and other cloud providers allowing customers to run workloads across multiple clouds. DigitalOcean's Kubernetes Service or DOKS for short now scales up to a thousand nodes supporting complex workloads with optimized network routing for enhanced speed and reduced latency. Developed with heavy customer inputs, this enhancement allows for infrastructure scaling to handle unexpected traffic surges with minimal manual effort. DOKS provides robust cluster creation with optimized default settings, several GPU and CPU droplet choices and integrated cloud resources enabling customers to manage large fluctuating workloads while maintaining high availability and performance as their DigitalOcean usage grows. Our managed database offerings for MySQL and PostgreSQL now feature significantly expanded scalable storage options. Effective in Q1, we have doubled the storage for managed MySQL plans to 20 terabytes. Managed PostgreSQL now supports up to 30 terabytes also doubling from its previous capacity. These enhancements enable our customers to seamlessly scale their database storage as their businesses grow accommodating both increasing demands of existing workloads and also migrations from self-managed databases with greater flexibility. Another product release that I want to highlight is network load balancing which was developed in response to strong demand from our larger Digital Native Enterprise customers. It enables companies to distribute traffic efficiently across multiple servers. This feature automatically scales resources increasing capacity during peak loads and decreasing it during slower periods. In Q1, we augmented these product innovations with increased support and engagement of our top customers with complementary go market motions. We expanded named account coverage to our top 3,000 customers by revenue which is double the coverage we had in 2024. We now have account team coverage for our top 3,000 accounts that includes a technical account manager who ensures that these customers leverage our platform to the fullest, a solution architect who helps with the actual adoption and a growth account manager who manages the overall relationships and looks for new workloads run on DO. This new named account engagement model and all the new product innovations enabled us to accelerate the traction with rapidly scaling and larger Digital Native Enterprise customers. To raise the visibility of these advanced features, we also launched a new webinar series called Sale to Success to drive product awareness and adoption featuring real world case studies and topics including the best practices in migrating workloads to DO and building real world applications using our Gen. AI platform using advanced capabilities like guardrails, AI knowledge bases and so forth. We're also publishing numerous case studies and are averaging about a case study a week to provide reference materials on how our Digital Native Enterprise customers are taking advantage of the expanding breadth of our platform. On the last call, I talked about a new migrations program and a small dedicated team to support it. And I'm very pleased to share that in Q1, we facilitated 79 migrations to the Digital Ocean platform. While these workloads will continue to grow in footprint, the average annual run rate from these migrations is already in the tens of thousands of dollars. Our migrations team along with specialized partners help these customers with planning, architecture and the actual technical work to make these migrations smooth and ensure that the most appropriate architecture is deployed to get the best ROI from our platform. In one such example, we want all workloads for ProMobi, a SaaS company known for its solutions in enterprise mobility management that hosts electronic protected health information or ePHI workloads on this solution. AppRite, an open source platform that helps developers quickly build and scale back end applications, signed a two year commitment with us in Q1. Their platform supports core back end services like authentication, databases, storage and messaging across multiple frameworks and languages. AppRite chose Digital Ocean over hyperscalers due to our superior price performance and our ability to rapidly deploy spaces in their preferred geographic regions. Another example of a customer that has rapidly adopted our new enterprise grade features is Centra, a leading eCommerce platform that leverages our role based access control, droplet auto scaling, global load balancers, VPC peering and more. Now turning to our AIML initiatives which is covered in page 7 of our earnings deck, we are progressing on our strategy of democratizing access to AI. I strongly believe that we are entering an era of AI everywhere in which every software application is going to have AI as a core component of how it functions. For our target customers, the digital native enterprises, this translates into a heavy use of AI in inferencing mode. The strong growth of AI in Q1, the majority of our customers' AI workloads are now in inferencing mode, giving us an early glimpse into an AI world dominated by use cases that are serving the needs of end customers and solving real world problems. To take advantage of the growing traction that we are seeing with inferencing workloads, we are optimizing our AI stack to serve inferencing by continuing to deploy capabilities across the infrastructure, platform and AI agent layers of our stack. Let me break out our advancements down a little bit more starting with the infrastructure layer. In Q1, we announced that DigitalOcean customers now have access to NVIDIA HGX H200 GPUs. Our deployment of these servers allows our customers to use them as standalone machines or multi-node clusters. Deepening our AMD partnership, in Q1, we now have access to a highly performant and cost-effective solution for AI inferencing workloads with the AMD Instinct MI300X GPUs with Rockum software. These leading-end GPUs are now available in single-tenon bare-metal configurations for customer seeking control and raw computing power to power AI inferencing. The demand is outpacing the supply for our AI products that leverage these leading-end GPU types, NVIDIA HGX H200s and AMD Instinct MI300X GPUs, which is further validation of our decision to invest in this growth capital and add material incremental capacity through our Atlanta data center. One real world example of a customer already leveraging our NVIDIA HGX H200 service offering is an emerging AI startup focused on developing next-generation search and recommendation solutions for e-commerce. This customer runs AI searches that scan billions of items and websites in real time, delivering curated recommendations tailored to their customers' fashion needs, and transforms search results into stunning visual recommendations. All of this is powered by DigitalOcean's NVIDIA HGX H200 GPUs. Another example on the AI infrastructure side is Windborne, a company whose mission is to help mitigate and manage the destructive aspects of climate change, extreme weather, and weather uncertainty. They achieve this by instrumenting the environment and advancing weather forecasts. Windborne leverages DigitalOcean's GPU droplets to build a record-breakingly accurate, deep learning-based global medium-range forecast model called WeatherMesh, which predicts wind speed, temperature, dew point, cloud cover, precipitation, geo-potential height, and more. Moving up the stack to the platform layer, I'm very excited about the progress we are making and the adoption we are driving on our Gen. AI platform, which is our fully managed solution designed to help digital native enterprises build and scale generative AI applications with ease. It now supports -the-art models from providers like Anthropic, Meta, Mistral, DeepSeq, OpenAI, and others, and offers advanced capabilities such as retrieval-augmented generation, function calling, secure guardrails, and more to ensure reliable and context-aware outputs. Developers can now integrate our Gen. AI into their workflows using APIs or embed chat interfaces directly into their applications. The platform also includes serverless model endpoints, vector database integration, and token-based billing allowing companies to go from prototype to production without managing complex infrastructure. While this platform is still in beta, we already have over 5,000 customers leveraging the platform, and over 8,000 agents have been created on it since announcing it in January. More than 80% of our users for this platform are existing DigitalOcean customers, clearly showing the potential that we have within our existing customer base. One such customer example is Phoenix Secure, a leading India-based GPS tracking and fleet management provider. They leverage the DigitalOcean Gen. AI platform to create and integrate sales AI agents into their GPS tracking platform to enhance lead management. Now let me also cover the AI agent declare. One of my favorite case studies on impactful AI agent applications is our own cloud-based copilot offering, which is currently in public preview. Cloud-based copilot is an AI-powered assistant integrated into our managed hosting platform that is designed to streamline server management and optimize website performance for growing small and medium businesses. This helps our customers automate tasks, monitor performance, and provide them with insights to help keep their websites up and running smoothly. Cloud-based copilot currently has over 250 customers leveraging the tool with over 90% accuracy rate. One specific customer leveraging cloud-based copilot is Create, a web design agency that specializes in creating and maintaining websites to effectively represent a client's brand. Create has been able to improve productivity by leveraging the insights feature to quickly and accurately identify issues that otherwise would have been only found, if found at all, through manual processes and review of logs. Another example is Courtesy, a digital marketing agency based in Australia that specializes in helping small businesses enhance their online presence through personalized and strategic digital solutions. Cloud-based copilot provides precise insights that empower Courtesy to quickly pinpoint and resolve e-commerce store issues, cutting problem-solving time from hours to just minutes. Let me now give you an update on the financing matters. In addition to the great progress we have made on top-line growth initiatives, we have also made material progress on our balance sheet and capital structure priorities. We announced this morning that we have taken the first step in addressing our outstanding 2026 convertible debt, having entered into a new, secured five-year credit facility agreement of $800 million, with a $500 million term loan aid that we will leverage to refinance a portion of our existing convertible notes. Matt will walk you through more details on our financial results, refinancing actions, and guidance later in the call. In closing, DigitalOcean's Q1 2025 demonstrates significant progress in executing the strategy we outlined at our recent Investor Day. We achieved accelerated revenue growth, consistent improvement in net dollar retention, and substantial advancement in our strategy to scale with digital native enterprises. Our product innovation remains strong, with over 50 new releases specifically designed for the sophisticated needs of our growing digital native enterprise customers. Notably, we are also observing a clear increase in inferencing, signifying the evolution of customer workloads towards practical real-world AI applications and strong adoption of our Gen. AI platform. Strategic -to-market investments and product innovation drove a 41% -over-year increase in revenue from customers spending over $100,000 annually. These results demonstrate clear progress towards our strategic goals and bolster our confidence in achieving our ambitious long-term objectives. Additionally, we have proactively started addressing our financing strategy by initiating debt refinancing, positioning us for sustained growth with the growing needs of our digital native enterprises. The momentum generated in Q1 provides a solid base for the remainder of the year and underscores our mission of simplifying cloud and AI so that digital native enterprise customers can focus on creating software that changes the world. Thank you, and now over to Matt.

Thanks, Patty. Good morning, everyone, and thanks for joining us today. As Patty discussed, we are very pleased with our Q1 2025 performance as we continue to execute against our key strategic priorities and deliver strong financial results. In my comments, I'll walk through our Q1 results, provide an update on our balance sheet and financing strategy, and share our second quarter and full year 2025 financial outlook. Starting with the top line, revenue in the first quarter was $211 million, and annual run rate revenue, or ARR, was $843 million, both up 14% year over year. We added $23 million of incremental ARR in the quarter, which is 50% higher compared to incremental ARR in the same quarter last year. We continue to focus our product innovation and -to-market investments on our digital native enterprise customers, and the momentum we have generated with this target customer base continues to grow. In Q1, revenue from our customers, whose annualized run rate revenue in the quarter was greater than $100,000, who we refer to as scalers plus, and who represent 23% of overall revenue, grew 41% year over year, with a 27% year over year increase in customer count, as our largest customers continued their strong adoption of our core cloud and AI products. Q1 revenue growth was driven by improvements in both customer acquisition and customer expansion. The enhancements we've made to our product-led growth engine are paying off in improved customer acquisition, with revenue growth from customers in their first 12 months on our platform continuing to accelerate in Q1. Our product innovation and -to-market efforts are also having an impact on customer expansion, as our Q1 net dollar retention ticked up to 100%, up from 97% in the same quarter last year, which is a major accomplishment, as we have largely eliminated the net expansion head when we faced last year. We expect NDR to remain in a similar range as the last two quarters for the remainder of the year. Increasing customer expansion was also evident in increased average spend, as average revenue per user, or ARPU, grew at 14% year over year. Turning to the P&L, gross margin for the fourth quarter was 61%, which was 200 basis points higher than the prior year. The improved gross margin is driven by our ongoing cost optimization efforts, with revenue growth at 14% year over year outpacing cost of revenue growth of 8%, and by the improved utilization and extended useful life of our servers from five to six years. Adjusted EBITDA was 86 million, an increase of 16% year over year. Adjusted EBITDA margin was 41% in the first quarter, approximately 100 basis points higher than the prior year. As shown in our current results and historical adjusted EBITDA margins, we continue to balance disciplined growth investments with ongoing gains in operational efficiency. Non-GAAP diluted net income per share was 56 cents, a 30% increase year over year. This increase is a direct result of expanding per share profitability by driving ongoing operating leverage and offsetting dilution through consistent share repurchases. GAAP diluted net income per share was 39 cents, a 160% increase year over year as we continue to both drive operating leverage and prudently manage stock-based compensation. Q1 adjusted free cash flow was effectively break even. As we discussed last quarter, our 2025 capital plan is heavily front unloaded, and when coupled with normal Q1 specific cash outflows, caused Q1 adjusted free cash flow to be significantly lower compared to Q4. While the lower Q1 adjusted free cash flow level was expected and is fully contemplated in our projected 16 to 18% free cash flow margins for 2025, it does warrant an explanation of how we view growth investments and how they have been and can be funded in the future. As a public cloud company, we invest each year in assets such as servers and network switches that underpin our simple and scalable cloud and AI solutions and the software that our customers consume for our infrastructure and platform as a service offerings. These assets have long useful lives and not only support our current customer usage and revenue, but also will support future customer usage and revenue for years to come. The amount of capital that we invest each year in these assets is a function of two drivers. The first driver of capital spend is the need to replace existing infrastructure that has reached the end of its useful life. Each year we buy new equipment to replace age servers and networking gear that has been supporting our existing customers and their usage. This capital spend is considered maintenance capital as it is required to maintain the health and stability of current platforms and revenue. We have continued to improve our maintenance capital efficiency over time by extending the useful life of our infrastructure and by leveraging the natural improvements and price performance of compute and storage infrastructure over time. Maintenance capital is generally less than 20 to 30 percent of our annual capital program or approximately five percent of revenue in a typical year. This is an important point for us to emphasize as it implies that our steady state adjusted free cash flow margin can be approximated by including only our maintenance capital in our adjusted free cash flow calculations. For reference, in 2024 this would have reflected a steady state adjusted free cash flow margin in the mid-30s. This maintenance capital dynamic, where a small portion of annual capital is required to support the existing business, is a sign of strong economics and is similar to what you see in data center and tower companies where very little capital is required to maintain their profitable platforms. The second and primary driver of capital is the need to provide incremental capacity for both existing customers as they expand their usage and for the new customers that we acquire. This capital spend is considered growth capital and it enables growth not only in the current year but also in the years to come. Paybacks on our growth capital are attractive with core cloud growth capital paying back in less than two years and AI growth capital having paybacks around three years. The amount that we spend on growth capital will vary from quarter to quarter based on our demand outlook and deployment timing but it's typically at least 70 to 80 percent of our capital program and approximately 15 percent of revenue. As the company grew from the IPO to 840 million in ARR, we elected to fund all of our maintenance and growth capital ourselves using our balance sheet and strong cash flow generation to buy and own servers and other equipment that we use to run our business. In fact, all of the company's capital expenditures since IPO have been funded by organic cash generation alone. As the 1.5 billion in convertible debt and the 723 million net proceeds from the IPO were all effectively used to fund 1.6 billion in share repurchases, over 450 million in M&A and repayment of approximately 260 million of debt. Looking forward as we work to reach and exceed a billion in revenue, it is even important to understand the dynamics of our growth capital investments. Our strategy is squarely focused on both serving larger digital native enterprises and pursuing our differentiated AI opportunity. Both of these initiatives create opportunities for us to accelerate our growth as we are seeing and winning larger workloads, individual customers and partnership opportunities than we have seen in the past as evidenced by the 20 million plus two-year commitment with the With these larger growth opportunities come more and longer customer commitments, but also larger capacity and capital requirements. It also changes the dynamics of how we plan for and provision for growth as we can no longer rely solely on broad utilization trends to trigger growth capital investments and instead have to have capacity available or be quickly able to deploy it to meet the needs of rapidly growing enterprises across both our core cloud and AI platforms. Said differently, when we have an opportunity to win a large workload, customers are willing to make long-term commitments, but they expect that the capacity is immediately available, which requires us to have capacity in front of demand more so than we have needed in the past. The investments we made in Q1 to add capacity in Atlanta are a great example of this upfront growth capital investment. With Atlanta, we are bringing on a larger amount of incremental capacity to serve a growing AI pipeline and we are doing so in a lower cost facility that will improve our long-run gross margin profile. As we look ahead at our growth potential in second half of 2025 and beyond, we anticipate an increasing portion of our growth to come from our larger digital native enterprises and from larger interesting or innovative businesses, both of which will come with more committed contracts. To accelerate growth beyond our current outlook while maintaining healthy free cash flow, we are actively evaluating adding additional funding tools for growth capital that are similar to those currently deployed by our public hyperscaler peers. With our plan to have fully addressed our balance sheet by the end of this year and with our ongoing adjusted free cash flow generation, we certainly can and will continue directly funding growth capital ourselves. However, we are also exploring adding additional financing options to our funding toolkit, where we could leverage a strong appetite from capital partners to support cloud and AI growth capital investment through leasing arrangements. Pursuing such a strategy would enable us to maintain or improve our strong cash flow generation while also reducing the upfront capital required to take advantage of the tremendous growth potential we see in both serving larger digital native enterprises and growing AI inferencing workloads. We are early in this evaluation and would only leverage this financing tool if it enabled us to accelerate growth beyond our current outlook. We will share more on this potential strategy as we advance our thinking over the coming months and quarters. Shifting back to Q1 results, we continued to maintain material cash and cash equivalents and ended the quarter with $360 million in cash. We continued to execute our share repurchase program in the quarter with $59 million of repurchases in Q1, buying back approximately 1.6 million shares. This brings our cumulative share repurchases since IPO to 1.6 billion and 34.1 million shares through March 31st of 2025. At the end of Q1, we had $23 million remaining on our share repurchase authorization. We remain well positioned to continue investment in both organic growth and share repurchases while we actively address our existing debt. On the debt front, we announced this morning that we have entered into a secured five-year credit facility agreement consisting of a $500 million nine-month delayed draw term loan A, as well as a $300 million revolving credit facility. This new loan bears interest on the drawn amount in the range of SOFR plus .75% or just over 6% based on the starting net leverage. We will use the proceeds from this facility to refinance a portion of our existing convertible notes that are maturing in December 2026. This loan is the first step in 2025 to fully address the 2026 convert before the existing facility goes current. With our strong balance sheet, growing adjusted EBITDA, and cash flow generation, we have multiple attractive options available to us that we are considering, including convertible debt, term loan B, and high yield options. We will continue to evaluate these options over the balance of this year to fully address the 2026 convert and optimize our long-term cost of debt. Moving on to guidance, I will now share our financial outlook for the second quarter of 2025 and for the full year. For the second quarter of 2025, we expect revenue to be in the range of 215.5 to 217.5 million, representing approximately .5% -over-year growth at the midpoint. For the full year 2025, we are maintaining our revenue guidance in the range of 870 to 890 million, representing approximately 13% -over-year growth at the midpoint. Given our strong Q1 performance and our visibility into our customers' usage trends, we remain confident in our full-year guidance despite the uncertainty in the current economic and geopolitical environments. For the second quarter of 2025, we expect our adjusted EBITDA margins to be in the range of 38 to 40%. For the full year, we maintain our adjusted EBITDA margin guide, which is in the range of 37 to 40%. For the second quarter of 2025, we expect non-gap diluted earnings per share to be 42 to 47 cents based on approximately 103 to 104 million in weighted average fully diluted shares outstanding. For the full year 2025, we expect non-gap diluted earnings per share to be $1.85 to $1.95 based on approximately 104 to 105 million in weighted average fully diluted shares outstanding. Turning to adjusted free cash flow, we maintain our guided adjusted free cash flow margins for the full year at 16 to 18%. We intend to take advantage of the nine-month delay drop feature of our new $500 million term loan A and do not anticipate drawing until late in 2025 and as such do not anticipate material interest expense on that facility in 2025. Consistent with our historical guidance practice, we are not providing adjusted free cash flow guidance on a -by-quarter basis given it is heavily influenced by working capital timing as you saw in our Q1 results. That concludes our prepared remarks and we will now open

up the call Q&A. If you wish to ask a question, please press star followed by one on your telephone and wait for your name to be announced. That is star one if you wish to ask a question. We ask that you limit your questions to one per person so we are able to take as many questions as possible. Your first question comes from Jason Ada from William Blair. Your line is open.

Thank you. Patty, just on the GEN.AI platform, can you give us a sense of when it is expected to be generally available? I know it is still essentially like the beta situation now. And then just related to that, you talked about sort of the differentiated AI opportunity for DigitalOcean. Can you just walk us through how you think about DigitalOcean's differentiation within that AI landscape? Thank you.

Thank you, Jason. On your first question, yes, the GEN.AI platform we announced in January and we have been progressively adding a lot of new features while still in private beta and public beta now. We expect to go live sometime by end of Q2, beginning of Q3. It is just a function of how many additional capabilities we can add to the platform, making it super comprehensive for customers to be able to deploy real world agentic workloads on it. I gave several examples of companies that are leveraging it in production environments today. We are getting excellent feedback from customers, both our existing customers as well as new AI native startups and companies that are giving us excellent feedback. I gave some count as well in terms of 5,000 customers, 8,000 agencies are tremendous numbers for a product that is not even in GA currently. We are super bullish about the future of the GEN.AI platform and we feel our full... The second part of your question was what is our strategy and differentiation from an AI perspective? I have been talking about our IPA stack, infrastructure platform and applications. As I outlined in today's call, we are making good progress on all three layers. The best part about infrastructure layer is that a majority of the workloads that we are seeing now are on the inferencing side. What is important to understand on the inferencing layer is that it is powering real world use cases rather than just proof of concept or experimentation, which means it is the needs of end users either in a B2B scenario or B2C scenario. I strongly believe that with our infrastructure capabilities today, both on AMD and NVIDIA, we are differentiating ourselves in our ability to run a full stack cloud that powers inferencing. As I explained in the investor day, inferencing needs a lot more than just bringing GPUs online. Inferencing typically requires a full stack general purpose cloud, which is where we distinguish ourselves from a number of the other Neo GPU clouds that have emerged over the last few quarters. On the platform layer, we just talked about the GEN.AI platform. Our strategy there is to democratize the access and make it super, super easy for non-AI native companies to consume GEN.AI in their application stack. The proof is in the numbers I talked about, like over 80% of the traction today we are seeing is from existing Digital Ocean, Digital Native Enterprise customers who are not AI natives, but they recognize the importance of adding GEN.AI into their application. We are making it super easy to build sophisticated GEN.AI features into their platform. Finally, the agentic layer, our cloud based co-pilot is doing really well. We are getting real customer feedback. That should go into GA sometime in the next couple of months as well. Overall, that is our AI strategy to democratize access of AI, starting from inferencing on the infrastructure layer to GEN.AI platform and agents that will change the cloud experience. Hopefully that gives you a perspective on our infrastructure platform and application layer.

Your next question comes from the line of Pinchal and Bora from JP Morgan. Your line is open.

Oh great, thank you. Congrats on the quarter. Patty, maybe talk about just what are you seeing from a macro standpoint? Obviously there's a lot of uncertainty over there, but so far in April in Q2, are you seeing any change in customer buying behavior or any change in the top of the funnel? Are you seeing people deploy any cloud optimization efforts back again, both domestically and internationally?

Great, Pinchal, and thank you for the question. I'll give you the answer first. Whatever we are observing is reflected in our outlook that Matt talked about. Let me take a step back and remind everyone that our customers are digital native enterprises. We had really solid evidence in Q1 that our strategy around the digital natives, around builders, scalers, scalers plus, it's growing really robustly at 16%. For digital natives, cloud is a top line driver. We have very clear visibility into customer usage on a daily basis. We monitor several utilization trends across the world. We are seeing some pockets of customers that have unique impacts on their business. For example, ad tech is a vertical that we have seen that is a little bit more in a heightened sense of cautiousness. As you know, we don't have any vertical, geographic, or even customer concentration. Whatever we are seeing is baked into our outlook. The second part of your question, Pinchal, we have several leading indicators we look at. We look at the usage patterns of our large customers. We look at the usage patterns of the long tail of our customer base. We look at the top of the funnel in terms of new business acquisition through our self-service funnel. We look at the pipeline that is being generated by our sales team, but also from our partners. We look at our AI demand. From what we can see, we have taken a very appropriately cautious approach to projecting the outlook for the rest of the year because we don't know exactly how things are going to unfold. Given the lack of concentration of our customers and geography and vertical segments, we feel fairly confident in our full year guidance.

Your next question comes from Gabriella Borges from Goldman Sachs. Your line is open.

Hi, good morning, Patty, Matt. Thanks for the details. I'm observing a shift in how you're talking about the business from being mostly reactive to being a little bit more predictable and larger deals. Maybe talk to us a little bit about the 20 million multi-year deal that you signed in particular. How do you think about the potential for more deals like that? What does the conversation look like given how quickly AI is changing and inference in particular is evolving? How do you get to the point where a customer is comfortable committing to long term? What sort of roadmap discussion is that? Thank you.

Thank you, Gabriella. Great question. Yes, as I mentioned in my prepared remarks, we are having a lot of ad bats with these larger digital native enterprise customers. The example that I quoted will have more details as we start working on the implementation of that customer commitment. But taking a big step back and looking at the overall landscape, these conversations that we are having with customers for multi-year large commitment contracts is both on AI inferencing as well as on core cloud. I think a lot of the functionalities that we have released and the ones specifically that I highlighted this earnings call are all lending themselves to having these kinds of conversations and giving our customers confidence that they can now move larger workloads to our platform without having to be all or nothing. So the partner connect functionality, I specifically mentioned how it enables stage migration where you can run parts of the workload in multi-cloud scenario and move some of the heavier workloads to digital ocean in a staged manner. There are so many other things we are doing both on the core infrastructure side but also in our platform as a service with DOKS now scaling to a thousand nodes, larger storage and database capabilities with our MySQL and Postgres. It is a collection of all of these things plus the continuing maturity of our -to-market motion. That is why I specifically called out the webinars case studies even though they may sound very obvious and natural for a company like us to be doing that. These are some new muscles that we are exercising and also the enterprise sales motion that we now have putting our arms around our biggest customers and really give them true onboarding experience. So it is a collection of all of these things that are giving us better at bats and of course as the quarters go by we are getting better and better at converting a lot of these things and I just wanted to bring attention to it that this is not a blue bird by any stretch. We are actually starting to see these kinds of deals and hence we are also evolving our thinking in terms of what we need to build, how we need to support it, how we should sell these capabilities and Matt talked about how we should be financing these things going forward. So it is a whole company kind of conscious push towards getting more predictability into our platform especially as we scale with the the larger digital natives.

Your next question comes from James Fish of Piper Sander. Your line is open.

Hey guys just wanted to build off of Gabrielle's question a little bit there but with the need to increase capacity for new customers coming on, Matt how do you think about CapEx investments for the year and how much ARR is the pipeline for these large strategic deals for the year that requires this level of CapEx investments that have you kind of having to weigh all these options beyond just refinancing the 1.5 billion really?

Good question Fish. The CapEx that we accelerated into the first quarter and that we front-loaded into the first quarter was primarily around getting the Atlanta data center up and which gave us a tremendous amount of capacity. That capacity is what underpins the growth projection and the revenue outlook and the incremental ARR for 2025 and as Patty indicated with that one large customer we have the opportunity to fill it in chunks as well as using kind of the more on-demand AI capabilities with our GPU droplets and other capabilities around the GEN.AI platform. So as we think about the CapEx requirements going forward again we're very comfortable with the estimates that we had of the capital we need for this year and the revenue projections that we have for this year but as we think about it over a longer period of time you got to come back to the fact that we are very very focused on driving revenue growth and doing so while generating strong pre-cash flow margins and as we think about some of the lumpier potential needs for the for capital around that when we win some of these bigger customers that's why we're thinking about tools like hey well we could lease the you know some of the contemplating because we can fund what we're already contemplating you know very very cleanly within the free cash flow margins that we've articulated but as we see bigger and bigger opportunities we want to make sure that we have the flexibility to pursue those and so we'll add some you know financing tool tools to our toolkit to be able to accommodate that so that we can both accelerate growth and you know not only maintain but even potentially improve the the free cash flow generation of business.

Your next question comes from Tom Blakely from Cantor. Your line is open.

Hi thanks for taking the question and congratulations on the the uptick in demand here maybe. Just building off of Mr. Fish questions here what you know what kind of changed from the April 4th Analyst Day in terms of what you're seeing in the market you know timing I think from an element would be helpful here. What type of like uptick you know in accelerated growth you know in the out year like you know are you are you kind of seeing from this uptick and what would the makeup be you know would it would it be more recurring revenue or would it be more consumption based from the GPU base just some a lot more color there just in terms of this what are you seeing in terms of the uptick of these large deals and potential needs for increasing those catbacks that'd be helpful. Thank you.

What I'd say is and I'll tie back to what Gabriella had asked earlier which is we're now at a point you know we've got through investor day we've got a lot of the AI capabilities in place we're observing the the rapid changes in the market and the shift towards inferencing. Majority of our AI revenue right now is inferencing and again we feel very good about the the near term outlook of the business despite the economic kind of uncertainty but as we think about 26 and 27 and beyond and we think about okay how do we you know position ourselves to take advantage of even accelerating the growth beyond what we articulated that investor day we're just thinking like what are the physics of that and how would we do that and how would we we both take advantage of some of these larger lumpier deals while while maintaining our free cash flow or even improving it and that's why we're thinking about the you know some of these other these other structures and so the the demand as you know we one we didn't have the Atlanta data center until just recently literally in the last month or so and so a lot of the bigger opportunities you know we didn't have the ability to win those because we didn't have capacity available and and so you know for us as we've we've turned that capacity up we've been able to you know get a big win already that's what's really accelerating the the thinking about okay well we've we've got a we feel good about 2025 but we got to start planning and thinking about the ways in which we can we can position ourselves to grow beyond what we had communicated in investor day in 2026 and beyond and that's that's why we're you know considering the things that we're considering

Your next question comes from Kingsley Grave from Campcore Humanity. The line is open.

Hi thank you. On the named account engagement model how many accounts have you targeted today and then how are you evaluating expanding that program to more prospects as you continue to see nice expansion results with those customers?

Yeah hi Kingsley. So right now we are targeting our top 3,000 spenders and that list has expanded as I mentioned from last year we covered 1,500 exiting the year so we just expanded coverage. So we are looking at several leading indicators to inform us when we start scaling it further. My philosophy is always to be in the face of maximizing the ability to engage with these companies. We also have a different propensity based engagement model with another 5,000 or so accounts based on their propensity to spend based on their demographics their usage of certain aspects of our platform and so forth. So think of them as 5,000 customers that look like our top 3,000 who have the propensity or the potential to be scalers plus or spend $100,000 or more on our platform. We are proactively engaging with them and bringing the goodness of our platform to these customers. So between these two I expect us to be busy for the remainder of the year. We are still trying to ensure that we have the right sales enablement model, the right sales rep and productivity metrics and things like that before we plan to expand that because we are getting to a point where we can predict exactly what the productivity of a single rep can be and making sure that we are able to scale that to a reasonable degree will give us the confidence to invest more in the future. But for this year we want to ensure that we are nailing these two motions.

Your next question comes from the line of Josh Bear from Morgan Stanley. Your line is open.

Great, thanks for the question. A really interesting dynamic to explore the alternative financing if it would enable growth to accelerate beyond your current outlook. Just wondering what you're seeing from the supply constraint side if you could maybe touch on GPUs but also more broadly on the leasing market how tight it is and how that might come into things.

Yeah Josh, on the supply side we remain kind of I'd say in a real healthy position from a supply standpoint. We don't order GPUs or CPUs in such massive quantities that we're having to get in line behind super large orders and in general the market as I'm sure you guys have heard, it's a lot less supply constrained from a GPU standpoint than it was last year. So we've not had any issues with getting a new capacity and we have a variety of sources. We've got four different global OEMs that we can access both NVIDIA and AMD GPUs from and clearly a lot of sources for CPUs. So we don't really worry too much about the supply chain side on the infrastructure side. In terms of the leasing alternatives there's a tremendous amount of interest from whether it's PEs or its other kind of capital providers to enter into leasing or similar arrangements. There's a lot of money around the globe that is wanting to be put to work in support of AI infrastructure in particular but certainly in our case it'd be AI and it'd be GPU and CPU. So there's a lot of different alternatives and part of the reason we're bringing it up now proactively is that we're engaging in some of these calls and it gives us the ability to talk to a lot of different people and explore options. I just want to reiterate though we don't need to do this to deliver the growth rate that we're delivering now. We generate a ton of cash. We've got a really good free cash flow profile. We're going to take care of our balance sheet in the convert by the end of this year. We're in a very very good position. This is a very good position to be in. We're not going to be able to do this without having to compromise the near-term free cash flow. So that's why we're interested and we think there's a lot of counter priorities out there that would be supportive of that kind of incremental addition to our funding strategy.

Great, thank you.

Your next question comes from Mark Chang from Citi. Your line is open.

Hey great, thanks guys for taking the question. So it'll be nice to see the NDR improvements and traction with the enterprise cohort but really you're holding I guess like S&M or sales and marketing spend pretty steady. So can you number one give a sense of how you're really able to achieve this incremental level of leverage especially given the new programs you're already running and I guess like customer behavior changes relative to your expectations. And number two, how should we really think about the spend trajectory from here and when should we maybe see an acceleration of those sales and co-market investments? Thanks.

Yeah, so I can start Mark. Thank you for the question. So I just answered the question from Kingsley on sales and marketing and our philosophy to investment there. I think we are still early in this cycle in terms of understanding the best ways to serve our customers. Largely our customer acquisition engine has been from self-service funnel and now we are just expanding it to additional motions like adding a channel partner program, getting a small but mighty team in terms of AI outbound sales and also expanding a couple of other partnership funnels. But we are learning very very rapidly what it takes to A, bring in new business through these channels but also leverage this named account model and farming to expand the footprint of our existing customers. So there's a lot of learning ahead of us in the spirit of nailing some of these unit economics so that we understand exactly what the points of leverage are and feel conviction to invest behind this to drive expansion even further. And we also want to be appropriately cautious given what our customers are dealing with in today's economic climate. I believe there are two major factors going on. One is the economic dislocation that is happening but also more importantly a technology dislocation which is largely positive for digital native customers and they are going to be more technology hungry as part of this. So we are very cautiously observing these things and we will invest at the right time behind the right unit economics to get more leverage and drive expansion and new business appropriately.

As we are at the top of the hour I would like to thank our speakers for today's presentation and thank you all for joining us. This now concludes today's conference. You may now disconnect.