Datadog, Inc.

Good day. Thank you for standing by. Welcome to the third quarter 2025 Data Dog Earnings Conference call. At this time, all participants are in listen-only mode. After the speaker's presentation, there will be a question and answer session. To ask a question during this session, you will need to press star 1-1 on your telephone. You will then hear an automated message inviting your hand is raised. To withdraw your question, please press star 1-1 again. Please be advised that today's conference is pre-recorded. I'd like to hand the conference over to your first speaker today, Yuka Bodrick, Senior Vice President of Investment Relations. Please go ahead.

Thank you, Marvin. Good morning, and thank you for joining us to review DataDog's third quarter 2025 financial results, which we announced in our press release issued this morning. Joining me on the call today are Olivier Pommel, Datadog's co-founder and CEO, and David Ochsler, Datadog's CFO. During this call, we will make forward-looking statements, including statements related to our future financial performance, our outlook for the fourth quarter and the fiscal year 2025, and related notes and assumptions, our growth margins and operating margins, our product capabilities, and our ability to capitalize on market opportunities. The words anticipate, believe, continue, estimate, expect, intend, will, and similar expressions are intended to identify forward-looking statements or similar indications of future expectations. These statements reflect our views only as of today and are subject to a variety of risks and uncertainties that could cause actual results to differ materially. For discussion of the material risks and other important factors that could affect our actual results, please refer to our Form 10-Q for the quarter ended June 30, 2025. Additional information will be made available in our upcoming Form 10-Q for the fiscal quarter ended September 30, 2025, and other filings for the SEC. This information is also available on the Investor Relations section of our website, along with a replay of this call. We will discuss non-GAAP financial measures, which are reconciled to their most directly comparable GAAP financial measures, in the tables in our earnings release, which is available at investors.datadoghq.com. With that, I'd like to turn the call over to Olivier.

Thank you, Catherine. and thank all of you for joining us this morning to go through our results for Q3. Let me begin with this quarter's business drivers. We have seen broad-based positive trends in the demand environment, with an ongoing strength of cloud migration and digital transformation. Against this backdrop, we executed a very strong Q3, both in new logo bookings and usage growth of existing customers. As a notable inflection, we saw acceleration of year-over-year revenue growth across our non-AI customers. And the sequential usage growth for non-AI existing customers was the highest we have seen going back 12 quarters. This growth was broad-based as our customers are adopting more products and getting more value from the Datadog platform. We also experienced strong revenue growth for our AI native customers and a broadening contribution to growth among those customers. There, too, we saw an acceleration of growth in our AI cohort in Q3 when excluding our largest customers. Looking at new business, contributions from new customers increased in Q3 in both the amount of new customer bookings as well as the revenue contribution from new customers. And as usual, churn has remained low, with gross revenue retention stable in the mid to high 90s, highlighting the mission-critical nature of our platform for our customers. Regarding our Q3 financial performance and key metrics, revenue was $886 million, an increase of 28% year-over-year and above the high end of our guidance range. We ended Q3 with about 32,000 customers, up from about 29,200 a year ago. We also ended with about 4,060 customers with an ARR of $100,000 or more, up from about 3,490 a year ago. These customers generated about 89% of our ARR. And we generated free cash flow of $214 million, with a free cash flow margin of 24%. Turning to platform adoption, our platform strategy continues to resonate in the market. At the end of Q3, 84% of customers were using two or more products, up from 83% a year ago. 54% of customers were using four or more products, up from 49% a year ago. 31% of our customers were using six or more products from 26% a year ago, and 16% of our customers were using eight or more products from 12% a year ago. Digital experience is an example of an area with no platform where our rapid piece of innovation is turning into tangible value for our customers. Our digital experience products include RAM, or Reuser Monitoring, to observe and improve application behavior in mobile and web apps, synthetics, to simulate user flows and proactively detect user-facing issues, and product analytics to help users connect application behavior to business impact. Over the years, we've built up product breadth and depth in this area, and that is being recognized in the marketplace. For the second year in a row, Datadog has been named the leader in the 2025 Gartner Magic Quadrant for digital experience monitoring. We're pleased that today these digital experience products together exceed $300 million in ARR. And this includes, in particular, a very fast ramp for product analytics, which has already seen adoption by more than 1,000 customers. We also want to call out our security suite of products, where we are executing and accelerating growth. Security ARR growth was in the mid-50s as a percentage year-over-year EQ3, up from the mid-40s we mentioned last quarter. We're starting to see success in including Cloud Theme in larger deals, and we'll get back to that in a bit in our customer examples. And we're seeing positive trends beyond cloud theme, including fast uptake of code security and an increasing number of wins in cloud security. Overall, we saw year-over-year growth acceleration in each one of our security products. Moving on to R&D. We continue to deliver on what is a very ambitious AI roadmap. We are seeing high customer interest in our Bits.ai agents, which we announced at our Dash user conference in June. We have now onboarded thousands of customers for preview access to the Bits.ai SRE engine. And as we prepare for general availability, we are getting very enthusiastic feedback on the time and cost savings enabled by Bits.ai. As one user recently told us, with Bits.ai SRE being on call 24-7 for us, mean times resolution for our services has improved significantly. For most cases, The investigation is already taken care of well before our engineers sit down and open their laptops to assess the issue. And this is not an isolated comment. We see the potential here for our agents to radically transform observability and operations. In LLM Observability, we recently launched LLM Experiments and Playgrounds for general availability, helping teams to rapidly iterate on LLM applications and AI agents. We also launched custom LLM as a Judge evaluations for general availability. which lets customers write evaluation prompts to assess application quality and safety. As an illustration of both in adoption, in the past few months, the number of LLM spans customers are sending to Datadog has more than quadrupled. And we are seeing a lot of interest in the Datadog MCP server. Our MCP server acts as a bridge between Datadog and AI agents, such as Codex, Powerpoint AI, Cloud Code, Piantropic, Cursor, GitHub Copilot, Google's ByBlock, and many more. Our previous customers are using real-time production data as a context to drive troubleshooting, root cause analysis, and automation in these agents. One user told us, the Datadog MCP server is a great tool. It enables me to get the last five minutes of my app and follow the spams and traces all the way to the root cause. I've never been more hooked on Datadog. So we see MCP adoption as a great way to cement Datadog even further into our customers' workflows. Finally, We continue to see a rising customer interest for next-gen AI observability, with over 5,000 customers sending us AI data through one or more of our AI integrations. On the topic of integrations, we are very proud to now support over 1,000 integrations, which we believe is unparalleled in our space. By using our integrations, customers correlate otherwise disparate data sources across Datadog products for deeper analysis. We can see from our customers' usage that this is a critical part of the Datadog platform. Our 32,000 customers use more than 50 integrations on average, while customers spending over $1 million annually with us use more than 150. And most importantly, as tech stacks evolve, we continue to update and expand our integrations so our customers can use Datadog to deploy new technologies with confidence. Last but not least, I wanted to give a shout out to our AI research team for the amazing work they have published. or a shorter open-weight time series forecasting model has been one of the top-down lows on Huijin's face over the past few months, and that is across all categories. It is very impactful as, among other things, the high quality of this work allows us to attract world-class AI researchers and engineers. Now let's move on to sales and marketing. We had a number of great new logo wins in customer expansion this quarter, so I'll go through a few of them. First, We ended a seven-figure annualized deal with a leading European telco, our largest ever land deal in Europe. This company's previous setup was expensive, inefficient, and wasn't scaling to meet their needs. By using Datadog, they expect to save over $1 million annually on tool costs alone, along with millions of dollars more in reduced operation costs, low engineering time, and avoidance of revenue loss. They will adopt 11 Datadog products to start, and will consolidate more than 10 commercial and open-source tools. Next, we landed a 70-year annualized deal with a leading financial risk and analytics company. The company's fragmented tooling has led to major incidents that sometimes took multiple days and hundreds of engineers to resolve. They plan to start with 11 Datadog products, including Oncall, Cloud Theme, and Bits.ai. and will replace 14 commercial, open-source, and hyperscale observability tools. Next, we landed a seven-figure annualized deal with a Fortune 500 technology hardware company. This is an exciting win for our new go-to-market motions targeting the largest and most sophisticated companies in the world. Datalog has been chosen as their strategic observability partner. and we are displacing commercial tools across observability, cloud theme, and incident response. This customer is starting with 14 Datadog products. Next, we signed a seven-figure annualized expansion with a 14,500 financial services company. This customer had pockets of siloed teams and data, including one business unit which manually hosted and maintained 93 separate instances of open source tooling. With this expansion, this company will adopt 15 Datadog products, including all three pillars in all of their business units. They will also replace their SIEM solution with Datadog Cloud SIEM in a seven-figure land deal for Cloud SIEM. And by bringing all their telemetry data into the Datadog platform, they expect better insights for their adoption of Bits.ai SRE agents today and Bits.ai Securities Analytics in the next year. Next, we signed a seven-figure analyzed expansion with a Fortune 500 heavy equipment company. With this expansion, this customer will replace its open-source log solution with Datadog Log Management and FlexLogs. They plan to adopt LLM observability, and their IT team is using cloud cost management to improve cost visibility and governance. Next, we will come back a leading vertical SaaS company with a seven-figure analyzed deal. By returning to Datadog, this customer benefits from more alignment with OpenTelemetry and will implement the incident and reliability processes that they were unable to execute on previously. Next, we signed a seven-figure annualized expansion with a major American carmaker. This customer is adopting Datadog products faster than previously expected, and this agreement supports their higher usage. With this expansion, they will adopt Datadog's incident management and on-call solution company-wide for a total of 5,000 users who support operational continuity across the business. Finally, We signed a nine-figure annualized expansion with a leading AI company. This company has been a long-time Datadog customer and has expanded their usage of multiple products, securing better economics for a higher commitment with an early renewal. Speaking of AI customers, we continue to help AI native customers, big and small, to grow and scale their businesses. And we continue to see this group broaden in number and size, with more than 500 AI native companies in this group. but 100 of which are spending more than $100,000 annually with Datadog, and more than 15 who are spending more than $1 million annually with us. While we know there's a lot of attention on this cohort, we primarily see it as an indication of what's to come as companies of every size and every single industry incorporate AI into their cloud applications. And that's it for another very strong quarter from our go-to-market teams, who are now very hard at work as we have a really exciting pipeline for Q4. Before I turn it over to David for a financial review, I want to say a few words on our longer term outlook. There's no change to our overall view that digital transformation and cloud migration are long-term secular growth drivers of our business. Meanwhile, we are advancing rapidly in AI, where we are incredibly excited about our opportunities. We're building a comprehensive set of AI observability products to help our customers tackle the higher complexity that comes with the technology. And we're building AI into Datadog, and I spoke earlier about the excitement our customers have for our Bits.ai agents. The market opportunity in cloud and AI is expected to grow rapidly into the trillions of dollars, and companies of every size and industry are looking to adopt AI to deliver value to their customers and drive positive business outcomes. So we're moving fast to help our customers develop, deploy, and grow into the cloud and into the AI world. With that, I will turn it over to our CFO, David.