Thank you and good morning. Thank you all for joining us today to review DigitalOcean's first quarter twenty twenty five financial results. Joining me on the call today are Patti Srinivasan, our Chief Executive Officer and Matt Steinfort, 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 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 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 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 twenty twenty five results. [indiscernible] 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 market for both core cloud and AI 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 $211,000,000 with our AI ARR continuing to grow north 160% year over year. Q1 net dollar retention rate or NDR improved to 100 for the first time since Q2 of twenty twenty three 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 our continued focus on our higher spending digital native enterprise customers increasing revenue from customers who were at $100,000 plus annual run rate up 41% year over year and to 23% of total revenue. This is valuable market growth rate 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 go 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 bps higher than the prior year, an improvement that came from cost optimization 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 spend was contemplated in our full year 2025 plan we remain on track for our full year free cash flow margin guidance. Having this new AI inferencing infrastructure in place, 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 $20,000,000 plus multiyear 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 multimillion dollar deals than we have in the past. While this is consistent with our strategy and we are about its near and long term growth potential, these deals require larger amounts of capacity to be available for the customer. To support these types of scaled global workloads, while maintaining our strong free cash flow generation, we are exploring additional funding strategies that Mad will explain in greater detail in his commentary that would increase our ability to more wrap 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're 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 and D spend a percentage of revenue which is a testament to DIO's engineering talent and our increasing use of AI for accelerating development and improving our operational posture. AI helped developers improving coding by up to 40% and we also saw gains in our fleet health 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, as 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, these enhancements 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 GPU CPU and GPU 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 increased support and engagement of our top customers with complementary go to market motions. We expanded named accounts, coverage to our top 3,000 customers by revenue, which is double the coverage we had in 2024. We now have accounting 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 deal. And building real world applications using our GenAI 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 DigitalOcean 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 won all workloads for ProMobi a SaaS company known for its solutions in enterprise mobility management, that hosts electronic protected health information [indiscernible] ePHI workloads on this solution. AppRight, 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 DigitalOcean 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 NFV enterprise grade features is Sentra, a leading e commerce platform that leverages our role based access control Droplet auto scaling, global load balancers, EPC peering and more.

Now turning to our AIML initiatives, which is covered in Page seven 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. With 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 April, we announced that our customers now have access to a highly performant and cost effective solution for AI inferencing workloads. With the AMD Instinct MI300X GPUs with ROCCM software. These leading edge GPUs are now available in single tenant bare metal configurations for customers seeking control and raw computing power to power AI inferencing. The demand is outpacing the supply for our AI product that leverage these leading edge 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 scans 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 GPU, Another example on the AI infrastructure side is WinBorn, a company whose mission is to help mitigate and manage the destructive aspects of climate change.

Extreme weather and weather uncertainty.

They achieved this by instrumenting the environment and advancing weather forecast. Windborne leverage 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, geopotential 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 GenAI platform. Which is our fully managed solution designed to help digital native enterprises build and scale generative AI applications with ease. It now supports state of the art models from providers like Anthropic, Meta, Mistral, DeepSeek, 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 GenAI 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 leveraged the DigitalOcean GenAI platform to create and integrate sales AI agents into their GPS tracking platform to enhance lead management. Now let me also cover the AI agentic layer. 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 two fifty 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 [indiscernible] 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've 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 2026 convertible debt having entered into a new secured five year credit facility agreement of $800,000,000 with a $500,000,000 Term Loan A 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 Q1 twenty twenty five 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, substantial advancement in our strategy to scale with the 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're also observing a clear increase in inferencing signifying the evolution of customer workloads towards practical real world AI applications strong adoption of our GenAI platform.

Strategic go to market investments and product innovation drove a 41% year over year 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 twenty twenty five performance as we continue to execute against our key strategic priorities 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 Starting with the top line. Revenue in the first quarter was $211,000,000 and annual run rate revenue or ARR was $843,000,000 both up 14% year over year. We added $23,000,000 of incremental ARR in the which is 50% higher compared to incremental ARR in the same quarter last year. We continue to focus our product innovation and go to market investments on our digital native enterprise 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 Scalars Plus, 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 twelve months on our platform continuing to accelerate in Q1. Our product innovation and go 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 headwind 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 and 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 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 86,000,000 an increase of 16% year over 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 $0.56 a 30% increase year over year. This increase is a direct result of expanding per share by driving ongoing operating leverage and offsetting dilution through consistent share repurchases. GAAP diluted net income per share was $0.39 160% 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 breakeven. As we discussed last quarter, our 2025 capital plan is heavily front end loaded. 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 offer. 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 aged servers and networking gear that has been supporting our existing customers and their usage. This capital spend is considered maintenance cap. As it is required to maintain the health and stability of current platform and revenue. 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% of our annual capital program or approximately 5% 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 calculation. For reference, in 2024, this would have reflected 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. This is second and primary driver capital is the need to provide incremental capacity for both existing customers 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 quarter based on our demand outlook and deployment timing.

But it's typically at least 70% to 80% of our capital program approximately 15% of revenue. As the company grew from the IPO to $840,000,000 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 the 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 $1,500,000,000 in convertible debt and the $723,000,000 net proceeds from the IPO were all effectively used to fund $1,600,000,000 in share repurchases over $450,000,000 in M and A and repayment of approximately $260,000,000 of debt. Looking forward, as we work to reach and exceed $1,000,000,000 in revenue, it is even more important to understand the dynamics of our growth capital investment. 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 partnership opportunities than we have seen in the past. As evidenced by the $20,000,000 plus two year commitment with the strategic customer and partner that Patti had referenced earlier in his remarks.

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 our 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 the second half of twenty twenty five and beyond, we anticipate an increasing portion of our growth to come from our larger digital native enterprise [indiscernible] 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 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 funding financing options to our funding toolkit. 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 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 continue to maintain material cash and cash equivalents, ended the quarter with $360,000,000 in cash.

We continued to execute our share repurchase program in the quarter, with $59,000,000 of repurchases in Q1 buying back approximately 1,600,000.0 shares. This brings our cumulative share repurchases since IPO to 1,600,000,000.0 and 34,100,000.0 shares through 03/31/2025. At the end of Q1, had $23,000,000 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 five year credit facility agreement consisting of a 500,000,000 nine month delayed draw term loan A as well as a $300,000,000 revolving credit facility. This new loan bears interest on the drawn amount in the range of SOFR plus 1.75%. Or just over 6% based on the starting new 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 twenty twenty five and for the full year. For the second quarter of twenty twenty five, we expect revenue to be in the range of 215,500,000.0 to 217,500,000.0 representing approximately 12.5% year over year growth at the midpoint. For the full year 2025, we are maintaining our revenue guidance in the range of $870,000,000 to $890,000,000 representing approximately 13% year 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 the current economic and geopolitical environments. For the second quarter of twenty twenty five, 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 twenty twenty five, we expect non GAAP diluted earnings per share to be $0.42 to $0.47 based on approximately $103 to $104,000,000 in weighted average fully diluted shares outstanding.

For the full year 2025, we expect non GAAP diluted earnings per share to be 1.85 to $1.95 based on approximately 104 to $105,000,000 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 delayed draw feature of our new $500,000,000 Term Loan A and do not anticipate drawing that facility until late in 2025. And as such, 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 quarter by quarter basis given it is heavily influenced working capital timing. As you saw in our Q1 results. That concludes our prepared remarks, and we will now open up the call to Q and A. First question comes from the line of Jason Ader from William Blair. Your line is open. Patty, just on the GenAI platform, can you give us a sense of when it's expected to be, generally available? I know it's still essentially like a beta situation now. And then then just related to that, you talked about, sort of the differentiated, I 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's 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. And 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.

So and I gave the some count as well in terms of 5,000 customers, 8,000 agencies are tremendous numbers for product that is not even in GA. Currently. So we're 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. So I've been talking about our IPA stack infrastructure platform and applications And as I outlined in today's call, we're making good progress on all three layers. The best part about our infrastructure layer is that a majority of the workloads that we are seeing now are on the inferencing side. And 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 serving the needs of end users either in a B2B scenario or B2C scenario. So 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 GenAI platform. Our strategy there is to democratize the make it super, super easy for non AI native companies to consume GenAI in their application stack. And the proof is in the numbers I talked about like over 80% of the traction today we are seeing is from existing DigitalOcean, digital native enterprise customers who are not AI natives, but they recognize the importance of adding GenAI into their application and we are making it super easy for them to build sophisticated GenAI features into their platform And finally, the agentic layer our cloud based co pilot is doing really well. We are getting real customer feedback and that should go into GA sometime in the next couple of months as well. So overall that is our AI strategy to democratize access of AI starting from inferencing on the infrastructure layer to GenAI platform and agents that will change the cloud experience. So hopefully that gives you a perspective on our infrastructure platform and application layer.

Your next question comes from the line of Pinjalim Bora from JPMorgan. Your line is open.

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 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. Pindulim, 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. So let me take a step back and and remind everyone that our customers are digital native enterprises. Right? And we had really solid evidence in Q1 that our strategy around the digital natives around builders, 16%. And for digital natives, cloud is a top line driver. Right? And we have very clear visibility into customer usage on a daily basis. We monitor several utilization trends across the world.

And we are seeing some pockets of customers that have unique impacts on their business. So for example, ad tech is a vertical that we have seen. That is a little bit more in a heightened sense of cautiousness. But as you know, we don't have any vertical geographic or even customer concentration. So whatever we are seeing is baked into our outlook. And to the second part of your question, Pindulim, 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 And 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 But given our 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 the line of Gabriela Borges from Goldman Sachs. 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 and larger deals. So maybe talk to us a little bit about the $20,000,000 multiyear deal that you signed in particular. How do you think about the potential for more deals like that? And what does the conversation look like given how quickly AI is changing and inference and particular is evolving? How does how 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.

Yes. Thank you, Gabriela. Great question. So yes, as I mentioned in my prepared remarks, we are have a lot of at bat with these larger digital native enterprise customers. And the example that I quoted, we'll have more details as we start working on the implementation of that customer commitment, But taking a step back and looking at the overall landscape, these conversations that we are having with customers for multiyear large commitment contracts is both on AI infra 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 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 work to DigitalOcean 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 1,000 nodes, larger storage and database capabilities with our MySQL and Postgres.

So it is a collection of all of these things plus the continuing maturity of our go to market motion. That is why specifically called out the webinars case studies even though they may be they may sound very obvious and for a company like us to be doing that, These are some new muscles that we are exercising. Also the enterprise sales portion that we now have putting our arms around our biggest customers and really get give them true onboarding experience So it's 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 larger digital natives.

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

Hey guys. Just wanted to build off of Gabriela's question a little bit there. But with the increased with the need to increase capacity for new customers coming on, how are you thinking 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 the 1,500,000,000.0, really?

Good question, Tish. The CapEx that we accelerated into the first quarter and that we 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 incremental ARR for 2025. And as Patti indicated with that one large customer, we have the opportunity to fill it in 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 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 free 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 some of the incremental gear if it accelerated our growth beyond what we're already contemplating. [indiscernible] can fund what we're already contemplating 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 financing tools to our toolkit. To be able to accommodate that so that we can both accelerate growth and not only maintain but even potentially improve the the free cash flow generation of the business.

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

Hi. Thanks for taking the question and congratulations on the uptick in demand here maybe.

Just building off of Mr. Fish questions here. [indiscernible] What kind of changed from the April 4 Analyst Day in terms of what seeing in the market? You know, timing, I think, from an element would be helpful here. What type of, like, uptick you know, in accelerating growth, you know, in the out year, like, 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 a lot more color there just in terms of this, what are you seeing in terms of an uptick of these large deals and potential needs for increasing this CapEx? That'd be helpful. Thank you.

What I'd say is, I'll tie it back to what Gabriela has asked earlier, which is we're now at a point we've got through Investor Day, we've got a lot of the AI capabilities in place. We're observing 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 near term outlook of the business despite the economic kind of uncertainty. But as we think about 2026 and 2027 and beyond and we think about, okay, how do we position ourselves to take advantage of even accelerating the growth beyond what we articulated at Investor Day. We're just thinking like what are the physics of and how would we do that and how would we both take advantage of some of these larger lumpier deals while maintaining our free cash flow or even improving it. And that's why we're thinking about some of these other these other structures. And so the demand as 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 we didn't have the ability to to win those because we didn't have capacity available.

And so for us, as we've turned that capacity up, we've been able to get a big win already. That's what's really accelerating the thinking about, okay, well, we've we got to we feel good about 2025, but we got start planning and thinking about the ways in which we can can position ourselves to grow beyond what we had communicated in Investor Day in 2026 and beyond. And that's why we're considering the things that we're considering.

Your next question comes from the line of Kingsley Grave from Canaccord. Your line is open.

Hi, thank you. On the named 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 several leading indicators to inform us when we start scaling it further. My philosophy is always to nail before scaling. So we are still going to be in the phase of maximizing the ability to engage with these 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 customers. Who have the propensity or the potential to be scalars 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 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 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 Baer from Morgan Stanley. Your line is open.

Great. Thanks for the question. 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 constraint side, 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?

Yes. Josh, on the supply side, we remain kind of, I'd say, in a real healthy position from a supply standpoint. We 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 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 CPU. So we don't really worry too much about the supply chain side on the on infrastructure side. In terms of leasing alternatives, there's a tremendous amount of interest from whether it's PEs or its other kind of capital providers to enter into kind of leasing or similar arrangements there's a lot of money that in around the globe that is wanting to be put to work in in support of AI infrastructure, in particular. But certainly, in our case, it would be AI and it would be GPU and CPU.

So there's a lot of different alternatives. Part of the reason that 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 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 and convert by the end of this year. We're in a very, very good position. This would enable us to grow faster than that without having to compromise the near term free cash flow. So that's why we're interested. We think there's a lot of counterparties out there that would be supportive of that kind of incremental addition to our funding strategy.

Great. Thank you.

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

Hey, great. Thanks guys for taking the question. So, obviously, nice to see the NDR improvements and traction with the enterprise cohort. Really, you're holding, I guess, like, know, s and m or sell the marketing spend pretty steady.

So can you, number one, give a sense of, you know, how you're really able to achieve this incremental level level of leverage? Given, you know, the new programs you're already running. And I guess, like, you know, customer behavior changes relative to your ex expectations. 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 go to market investments? Thanks.

Yeah. So I can start, Mark, you for the question. So I just answered the on sales and marketing and our philosophy to investment there. I think we are still early in the 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 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 that are going on.

One 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.