Datadog, Inc.

Good day and thank you for standing by. Welcome to the first quarter 2026 Data Dog Earnings Conference Call. At this time, all participants are in a listen-only mode. After the speaker's presentation, there'll be a question and answer session. To ask a question during the session, you'll need to press star 11 on your telephone. You will then hear an automated message advising your hand is raised. To answer your question, please press star 11 again. Please be advised that today's conference is being recorded. I would now like to turn the conference over to Yuka Broderick, Senior Vice President of Investor Relations. Please go ahead.

Thank you, Lisa. Good morning, and thank you all for joining us to review Datadog's first quarter 2026 financial results, which we announced in our press release issued this morning. Joining me on the call today are Olivier Plamel, Datadog's co-founder and CEO, and David Obstler, Datadog's CFO. During this call, we will make forward-looking statements, including statements related to our future financial performance, our outlook for the second quarter and the fiscal year 2026, and related notes and assumptions, 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 and similar indications of future expectations. These statements reflect our views 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-K for the year ended December 31, 2025. Additional information will be made available in our upcoming Form 10-Q for the fiscal quarter ending March 31, 2026 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.

Thanks, Yuka, and thank you all for joining us to go over a very strong start to 2026. Let me begin with this quarter's business drivers. I'm very pleased to say that our teams executed very well and delivered revenue growth of 32% year-over-year. accelerating from 29% last quarter and 25% in the year-over-quarter. We showed broad-based acceleration of revenue growth across cohorts, including both our AI and non-AI customers. Our AI-native customers cohort continued to grow and diversify rapidly, both in the number of customers we serve and the scale of those customers. And this quarter included new land deals with two of the world's biggest AI research teams, helping them improve and optimize their training workflows. I'll talk more about that in a bit. Even more impressive was the growth in our non-AI customers. Non-AI customer revenue growth accelerated again this quarter to meet 20% year-over-year, up from 23% last quarter and 19% in the year-over-year quarter. We think this is a sign of strong continued cloud migration, greater adoption of our products, and customers of all kinds accelerating their use of AI. Finally, 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 Q1 financial performance and key metrics, revenue was $1.01 billion, an increase of 32% year over year and above the high end of our guidance range. We ended Q1 with about 33,200 customers, up from about 30,500 a year ago, We also ended with about 4,550 customers with an ARR of $100,000 or more, up from about 3,770 a year ago. These customers generated about 90% of our ARR. And we generated free cash flow of $289 million, with a free cash flow margin of 29%. Turning to product adoption, our platform strategy continues to resonate in the market. For example, products up from 51% a year ago. 35% of our customers use six or more products up from 28% a year ago and 20% of our customers use eight or more products up from 13% a year ago. So we're lending more customers and delivering value across more products and our business continues to grow and Our total ARR now exceeds $4 billion, and our quarterly revenue exceeded $1 billion for the first time in Q1. This is a big achievement for all of us at Datadog, and is a product of years of investment in building and innovating for our customers. But we're still just getting started. Of our 26 products, five are over $100 million in ARR, and another three are between $50 million and $100 million in ARR. We're working hard to build and deliver further growth in those products. And this leaves 18 other products which are earlier in their life cycles. We believe each has a potential to grow to more than $100 million over time. Moving on to R&D, our engineers, enabled with the latest AI coding tools, are building rapidly to help our customers confidently and securely deploy their applications. So let me speak to a few of our product launches this quarter. Let's start with AI. As a reminder, we're talking about our AI efforts in two buckets, AI for Datadog and Datadog for AI. So first, AI for Datadog. These are AI products and capabilities that make the Datadog platform better and more useful for our customers. In March, we launched our MCP server for general availability. With MCP server, Developers access live production data to debug their applications directly in their AI coding agent, or IDE. We delivered BIT AI Security Agent, which autonomously manages Datadog cloud SIM signals, conducts in-depth investigations of potential threats, and delivers actionable recommendations. We've seen BIT AI Security Agent reduce investigations that could take hours to as little as 30 seconds. We also shipped BIT Assistant, now in preview, which helps customers search and act across Datadog using natural language balls. Moving on to Datadog for AI. This includes Datadog capabilities that deliver end-to-end observability and security across the AI stack. We launched GPU monitoring, enabling teams to understand GPU fleet utilization, workload efficiency, thermal and power behavior, and interconnect performance. This drives higher GPU ROI and operational reliability. Our customers continue to move forward with their AI activities, and we can see that in their usage of the Datalog platform. We now have over 6,500 customers sending data for one or more of our AI integrations. Though this is only 20% of total customers, they represent about 80% of our ARR. And our customers' usage of AI within Datalog platform continues to grow rapidly. Meet AI SRE agent investigations, have more than doubled from December to March. The number of spans sent to our LLM observability product nearly tripled quarter over quarter. The number of Datadog MCP server tool calls quadrupled quarter over quarter. And the number of beef assistant messages increased by a factor of 12 in that period. While we are aggressively building with and for AI, we also continue to expand the Datadog platform to deliver against our customers' increasingly complex needs. to speak to a few of these efforts. Last month, we launched experiments for general availability. Experiments work hand-in-hand with our feature flagging product and combine best-in-class statistical methods with real-time observability guardrails so companies can test for impact, choose among alternatives quickly, and ship with confidence. In addition, our customers now benefit from APM recommendations by analyzing telemetry data from application performance monitoring, resource monitoring, profiler, and database monitoring. APM recommendations automatically identify performance and reliability issues, and most importantly, explain how to fix them. And we announced our plans to launch our next data center in the UK. We see a large opportunity to serve our British customers as cloud adoption accelerates in regulated industries. Last but not least, We are pleased to have received FedRAMP High certification from the U.S. federal government. With this certification, we can now move forward with federal agency customers that require FedRAMP High to handle sensitive workloads. Meanwhile, we continue to expand our product offerings, go-to-market teams, and channel partnerships for public sector customers, both in the U.S. and internationally. So our teams were hard at work again. and we're looking forward to sharing many new products and feature announcements at our Dash User Conference on June 9th and 10th in New York City. Now let's move on to sales and marketing and highlight some of the deals we close this quarter. First, we landed two large deals, a seven-figure and an eight-figure annualized deal with a with the AI research divisions at two of the world's largest technology companies. These organizations are building and training the most advanced AI models in the world. It is critical for them to reduce engineering friction and increase training velocity. But fragmented internal and open source tooling made it harder to identify and solve issues and reduce engineering and research productivity. By using Datadog, both companies are accelerating their pace of innovation on their hyperscale AI training workloads. and this includes optimizing their workflows using GPU monitoring on large parallel GPU grids. Next, we signed a seven-figure annualized expansion for an eight-figure annualized deal with a leading online recruiting platform. This customer is centralizing on Datadog to reduce complexity, drive developer velocity, and improve efficiency. With this expansion, they will replace a standalone tool with Datadog LLM observability to correlate LLM signals with APM and user experience data. This customer will grow to 16 Datadog products, including Datadog MCP server. Next, we signed a seven-figure annualized expansion for an eight-figure annualized deal with a Fortune 500 bank. With this expansion, this customer will migrate their remaining log data into Datadog, fully replacing their legacy log vendor. Most notably, our flex logs give them granular control over cost while meeting strict compliance requirements. This customer uses 10 Datadog products, including Bits.ai SRE agent, to accelerate incident response with AI. Next, we signed a 70-year analyzed expansion with a leading global edge fund. This customer operates thousands of on-prem hosts and network devices. At that scale, their open source monitoring stack has become operationally unsustainable impacting portfolio managers and investment analysts. With this expansion, they will replace their entire on-prem observability layer with Datadog infrastructure monitoring and network device monitoring, and will have unified visibility across their cloud and on-prem environments. This customer will expand to 11 Datadog products. Next, we landed a six-figure annualized deal with a Fortune 500 insurance company. This company's fragmented observability stack led to long outages with incidents reported first by their customers instead of their tooling. By using Datadog and consolidating three legacy APM tools, they expect to move from reactive responses to proactive incident detection. They will adopt 10 Datadog products to start, including all three pillars and LLM observability. Next, we signed a 70-year annualized expansion with one of the world's largest travel groups in APAC. This customer was using Datadog on one business unit But in two others, they were juggling multiple tools and lacked actionable insights. By consolidating six legacy open source and cloud monitoring tools, the customers save money and improve platform resiliency and performance. This multi-year commitment positions Datadog as their strategic observability provider. And finally, we landed a six-figure annualized deal with a leading Latin American fintech company. This customer serves tens of millions of users across critical financial flows. Their rapid growth outpaced their fragmented front-end monitoring setup, and outages exposed them to financial, operational, and reputational risks. By adopting our digital experience monitoring suite, including RAM, synthetics, and product analytics, they now have full visibility over user activity. With the cost control they also previously lacked. This customer will start with five Datadog products. And that's it for our wins. Congratulations again to our entire go-to-market organization for a great Q1. Before I turn it over to David for a financial review, I want to say a few words on our longer-term outlook. We are pleased with the way we started 2026, as we support our customers' inflection in AI usage and application development, and as they lean into our AI innovations, including Bits AI SRE Agent, Bits AI Security Analyst, Bits Assistant, Datalog MCP Server, GPU monitoring, and many more. There is no change to our overall view that digital transformation and cloud migration are long-term secular growth drivers for our business. But we now have an additional secular growth driver with AI, as we help our customers deliver more value with this transformative new technology. Now more than ever, we feel ideally positioned to help customers of every size and every industry as well as all types of users, whether humans or AI agents, so they can transform, innovate, and drive value through AI and cloud adoption. And with that, I will turn it over to our CFO, David.