DigitalOcean Holdings, Inc.

All lines have been placed on mute to prevent any background noise. After the speaker's remarks, there will be a question and 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. And if you would like to withdraw your question, press star one again. Thank you. And I would now like to turn the conference over to Melanie Strait, Head of Investor Relations. Melanie, you may begin.

Thank you and good morning. Thank you all for joining us today to review DigitalOcean's second quarter 2025 financial results. Joining me on the call today are Patty 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 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 this 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 Patti.

Thank you, Melanie. Good morning, everyone, and thank you for joining us today as we review our second quarter 2025 results. We continue to make meaningful progress on the strategy we laid out at our investor day back in April. This is evidenced by our strong second quarter results and supported by the fact that we are raising our full year guidance on both revenue and profitability metrics. My comments today will include a recap of our Q2 financial results and an update on both our progress in product innovation and our enhanced go-to-market strategy across both core cloud and AI, which are enabling over 174,000 digital native enterprise customers to scale on our platform. Let me start with the second quarter financial results highlighted on slide 10 of our earnings deck. The growth momentum from Q1 continued into the second quarter, with revenue of $290 million growing 14% year over year. We saw excellent strength in our AI ML business, with revenue growing north of 100% year over year. Revenue from our Scalar Plus customers, or customers who were at $100,000-plus annual run rate during the quarter continued to see strong growth during the quarter at 35% year-over-year and increased to 24% of total revenue. Finally, we achieved incremental ARR in the second quarter of $32 million, our highest incremental ARR since Q4 of 2022 and the highest organic incremental ARR in over three years. Given our strong top-line performance in the first half of the year and our confidence in the second half outlook, we are raising our full-year revenue guidance range to $888 million to $892 million. We are also excited about the traction we are getting with larger customers and increase in committed contracts. I spoke last quarter about a multi-year $20 million plus committed deal, and this was a contributor to the material growth in our remaining performance obligation balance as we continue to seek and secure large multi-year deals with our higher spend customers and key strategic partners. Not only did our momentum carry over to the second quarter, but also the growth to come The growth continues to come with healthy profitability, including adjusted free cash flow of $57 million, which is 26% of revenue. As a result of this performance, we are raising our full year free cash flow guide to 17 to 19% of revenue, demonstrating our ability to accelerate revenue while maintaining attractive free cash flow margins. Turning to the balance sheet, we continue to make progress on our capital allocation priorities and remain on track to address the outstanding 2026 convertible debt prior to the end of this calendar year. Matt will go into further details on this front in his prepared remarks. Now let me give you some updates on the product innovation that we continue to deliver for our digital native enterprise customers, which you can see highlighted on slides 11 and 12 in the earnings presentation. During the quarter, we released more than 60 new products and features addressing the needs of our higher spend customers, which includes builders, scalers, and Scalar Plus customers, who now drive 89% of our revenue. Notably, 64 of our top 100 customers have adopted a product or a feature released within the last year, and 26 of the top 100 customers have adopted a new capability released within the last quarter. both clear proof points of the impact product innovation is having on our digital native enterprise customers. Let me now provide a few product highlights from the quarter starting with Core Cloud. This past quarter, we officially announced our Atlanta data center, and its resources are now available to all customers. As a reminder, this is our newest and largest data center. And it is purpose-built to deliver high-density GPU infrastructure optimized for AI inferencing, which requires a lot more than just GPUs. This data center has our core cloud stack, including compute, storage, and other cloud features that are critical to enabling AI-native customers to run full-stack applications powered by AI, and not just the training or inference part of their software. This agentic cloud data center infrastructure is a key differentiating factor for us over other Neo clouds as it provides a complete stack for running sophisticated AI applications that have comprehensive needs beyond GPUs. More on that a little later. During the quarter, we continue to build capabilities for larger digital native enterprises. These customers typically require high quality storage, especially for AI workloads. To support that requirement, we enabled NFS or network file systems for GPUs so that customers can run the most demanding GPU applications with access to higher performance object storage to meet the demands of enterprise workloads such as video streaming and data lakes. We also introduced two advanced networking features in public preview. Bring your own IP address or BYO IP and network address translation gateways, or NAT gateways. These are critical capabilities that will enable more and larger digital native enterprise workloads to migrate to DigitalOcean. BYO IP allows customers to use their existing publicly routable IP addresses on DO rather than having to acquire new DigitalOcean-specific IP addresses. This makes it easy for customers to lift and shift their workloads to our platform without requiring extensive changes to their applications, while NAP gateway allows the customer's resources to securely access the internet from within their virtual private cloud on the DEO platform. These innovations on the core cloud platform are enabling us to scale and win more workloads from our digital native enterprise customer base. To leverage that traction, we are complementing our industry-leading product-led growth motion with a small dedicated migrations team to support customers moving existing workloads from hyperscalers and other clouds to DigitalOcean's platform. And we facilitated 76 of these migrations during the quarter. One example of this is a company called Exitium, a next-generation cybersecurity provider delivering innovative, no-cost incident response as part of its fully managed Security Operations Center, or SOC, offering. Designed for businesses and managed service providers, or MSPs, Exciteum's managed SOC provides real-time threat detection, threat hunting, and incident response, all without the high cost typically associated with legacy solutions. Exciteum signed an 18-month contract with DigitalOcean, selecting the platform to migrate from other cloud providers due to our compelling total cost of ownership, performance, and ease of use, enabling Exciteum to deliver its cutting-edge cybersecurity solutions more efficiently and at scale. Servebee.host, a Scalar Plus customer that offers managed hosting specifically tailored for the Kraft content management system has already adopted our newly released network address translation gateway, enabling their customers to securely access the internet within their DigitalOcean Virtual Private Cloud. We're also very excited about the progress we're making on our AI ML platform, which we now call the DigitalOcean Gradient AI Agentic Cloud. which complements our full-stack general-purpose cloud. Slide 8 in the earnings presentation shows the power of having these two platforms side by side, enabling our customers to take full advantage of the integrated stack that is required to build and run AI-powered applications in the future. The Gradient AI Agentech Cloud has three components, Gradient AI Infrastructure, Gradient AI Platform, and gradient AI agents. Let me start with the gradient AI infrastructure, where we expanded our GPU droplets lineup significantly to now include eight major types, including the H, L, and RTX series GPUs from NVIDIA, and the latest Instinct series GPUs from AMD. Another major update that makes gradient AI infrastructure great for inferencing is a new inference optimized GPU droplet, which simplifies the setup and deployment of LLMs by leveraging Docker. And this new GPU droplet comes pre-configured with VLLM and includes built-in optimizations like multi-GPU parallelism, smart batching, faster and higher token generation, built-in support for hugging trace model downloads, speculative decoding, prompt caching, and multi-model concurrency so that customers can go from deployment to serving tokens in minutes on any GPU droplet without having to do all these steps manually. We recently announced a collaboration with AMD that provides DO customers with access to AMD Instinct MI325X GPU droplets in addition to MI300X droplets. These GPUs deliver high level performance at lower TCO and are ideal for large scale AI inferencing workloads. Another example of this growing collaboration between the two companies is the Gradient AI infrastructure powering the recently announced AMD Developer Cloud, which enables developers and open source contributors to test drive AMD instinct GPUs instantly in a fully managed environment managed by our gradient AI infrastructure. This enables developers to start AI development with zero hardware investment and accelerate the time to value in tasks like benchmarking and inference scaling. This further advances our mission of democratizing access to AI while maintaining the quality, performance, and flexibility our customers have come to expect from DL. Let's look at how customers are taking advantage of our gradient AI infrastructure. Featherless.ai is a serverless AI inference platform offering API access to an expansive and growing catalog of open-weight models, primarily hugging trace models like LAMA, Mistral, Gwen, DeepSeq, RWKB, and more. Featherless AI leverages DigitalOcean for its simplicity and price performance. And they were an early adopter of our AMD MI300X GPU droplets, which offer industry-leading price performance and ease of use for inference workloads. Another GPU droplet customer is Crye Bay AI, a digital native enterprise specializing in AI-generated documentation, which is used by 94% of the Fortune 500 companies. Scribe AI migrated their AIML training workloads to DigitalOcean from competitive cloud providers, and it's now leveraging DO's GPU droplets to build and train their process documentation and knowledge-sharing platform. Moving on to the next layer of our Gradient AI agentic cloud, we recently announced the general availability of DigitalOcean Gradient AI platform, which provides the industry's easiest and most cost-effective platform for developing production-grade AI agents with automated safety and security guardrails. The Gradient AI platform, as shown on the right side of slide eight of the earnings deck, is a one-of-a-kind platform that caters to the end-to-end agent development lifecycle or ADLC for short, enabling AI native, SAS, and any software application customer to build, test, deploy, monitor, and operate agentic AI software. Customers can use a rich set of proprietary and open source foundation models, including OpenAI, Anthropic, Mistral, DeepSeq, and LAMA as high performance serverless endpoints. These serverless endpoints automatically scale to meet real-time application demands, thus freeing customers from having to manage compute resources on their own. The Gradient AI platform provides built-in guardrails that verify AI behavior and new best-in-class agent evaluation framework to drive high accuracy and relevance of AI results. and a robust experimentation capability to deliver optimal AI performance. Over 14,000 agents have been created since announcing this platform, which is almost double the number of agents last quarter. More than 6,000 customers have leveraged this platform since January, with 30% of these customers being new to DigitalOcean. One of the customers leveraging our new Gradient AI platform is Quickest with a Q. a leading AI-powered collaborative workspace product that helps product, marketing, and sales teams generate strategy documents, campaigns, and playbooks using shared AI personas. Quickest leverages the Gradient AI platform to create persona-generating agents, enabling model comparisons and orchestrating tasks on the Gradient AI platform to fetch and summarize the markdown content. Quickest chose DigitalOcean because they needed a flexible and scalable infrastructure to support complex AI workflows, and they valued the simplicity of deploying agents and integrating them to the quickest product line with very little coding involved. Moving on to the gradient AI agents layer, our first commercial AI agent is the Cloudways Co-Pilot, which continuously monitors critical server components like the web stack, disk space, inodes, and host health to detect issues in real time, diagnose root causes, and deliver actionable recommendations faster than traditional alerting systems. An example of a customer leveraging this product is Mint Media, a full-service media and marketing company specializing in video production and digital marketing. Mint Media uses our cloud-based co-pilot GenAI agents to automatically detect and remediate web hosting issues. Mint Media manages over 180 websites and saw significant time savings by leveraging CloudBase Co-Pilot and the associated AI Power Insights and automated issue resolution. What previously required hours of manual debugging is now handled in minutes through the agent's detailed, actionable recommendations. In addition to the product innovations we delivered, we also made material progress on the go-to-market front during this quarter. From a new customer acquisition perspective, we saw meaningful progress at the top of the funnel from our product-led growth enhancements, with revenue from core cloud customers in their first 12 months significantly outpacing growth of prior years, which is a great leading indicator of future growth potential. Our direct sales motion and the strong ecosystem partnerships are driving more AI-native customers with large-scale inferencing requirements than we have ever seen in the past. Our growing success with these marquee customers is evident in the increased RPO that I mentioned earlier in my comments, and we anticipate this trend to continue as we scale out our AI capabilities. In closing, I am pleased both by the results of the second quarter and by the progress we are making on the strategy that we articulated at our investor day back in April. We maintained our top-line growth momentum from Q1 to Q2 while maintaining healthy profitability metrics, enabling us to raise our guidance across both revenue and profitability metrics for the fiscal year 2025. We delivered continued product innovation and both drove improved performance in our industry-leading product-led growth engine and continued to get traction with our direct sales go-to-market motion, especially for AI. We recently launched the Gradient AI platform into full general availability, a significant step in our offering to our customers a twin stack of cloud capabilities as outlined in slide eight of the earnings slide deck. In a single unified stack, we provide a mature, complete general purpose cloud, and on the other stack, a modern agentic AI cloud. These integrated stacks enable AI native customers to run inferencing at scale while taking advantage of the core cloud modules and digital native customers to build AI directly into their software applications without having to do the heavy lifting of dealing with AI infrastructure. With this unique twin cloud and AI stacks, We are getting increasing momentum with AI native companies with larger scale inferencing workloads, and we are expanding our partnerships with key ecosystem players in the AI domain. We are also making good progress on our balance sheet and refinancing priorities, positioning us for a strong 2026. Thank you, and I'll now turn it over to Matt.