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.

Thanks, Olivier. To start, our Q3 revenue was $886 million, up 28% year-over-year and up 7% quarter-over-quarter. To dive into some of the drivers of our Q3 revenue growth first, overall, we saw sequential usage growth from existing customers in Q3 that was higher than our expectations and the strongest in 12 quarters, in our non-AI native customer base. We saw year-over-year growth acceleration broadly across our business, including in new logos and existing customers, both enterprise and SMB, with customers across our spending bands, big and small, and customers in a wide variety of industries. Next, we saw strong and accelerating contribution from new customers, New logo annualized bookings more than doubled year over year and set a new record, driven by an increase in average new logo land size, particularly in enterprise. We believe we are starting to see the benefits of our growth of sales capacity. And we are seeing new logos ramping faster, contributing more to revenue growth. The portion of our year-over-year revenue growth that related to new customers was about 25% in Q3, up from 20% in Q2. Next, our AI native customers continue to exhibit rapid growth, while more customers in this group are growing to be sizable customers. As Olivier discussed, we extended the contract of our largest AI native customers. In addition, we now have more larger AI customers, including 15 of them spending $1 million or more annually with Datadog, and about 100 spending more than $100,000 annually. Year-over-year revenue growth from our AI native customers, excluding the largest customer, again accelerated in Q3. In Q3, this group represented 12% of our revenue up from 11% last quarter and about 6% in the year-ago quarter. I will note that over time, we think this metric will become less relevant as AI usage in production broadens beyond this group of customers. Our year-over-year revenue growth also accelerated amongst our non-AI native customers. In Q3, our revenue growth, excluding the AI Native customer group, was 20% year-over-year, accelerating from 18% year-over-year in Q2. And we have seen this trend of accelerating growth continue in October. Regarding retention metrics, our trailing 12-month net revenue retention percentage was 120%, similar to last quarter. And our trailing 12-month gross revenue retention percentage remained in the mid to high 90s. And now moving on to our financial results. Our billings were $893 million, up 30% year over year. Our remaining performance obligations, or RPO, was $2.79 billion, up 53% year over year. And current RPO growth was in the low 50s percentage year over year. Our strong bookings contributed to this acceleration of RPO. We continue to believe that revenue is a better indication of our trends in our business than billings and RPO. And now let's review some of the key income statement results. Unless otherwise noted, all metrics are non-GAAP. We have provided a reconciliation of GAAP to non-GAAP financials in our earnings release. First, gross profit in the quarter was $719 million, and our gross margin was 81.2%. This compares to a gross margin of 80.9% last quarter and 81.1% in the year-ago quarter. As previously mentioned, we continue to see the impact of our engineers' cost-saving efforts in Q3 as they deliver on our cloud efficiency projects. Our Q3 OPEX grew 32% year-over-year, down from 36% last quarter. We continue to grow our investments to pursue our long-term growth opportunities, and this OPEX growth is an indication of our execution on our hiring plan. Q3 operating income was $207 million for a 23% operating margin compared to 20% last quarter, and 25% in the year-ago quarter. And now turning to our balance sheet and cash flow statements, we ended the quarter with $4.1 billion in cash, cash equivalents, and marketable securities. And cash flow from operations was $251 billion in the quarter. After taking into consideration capital expenditures and capitalized software, free cash flow was $214 million for a free cash flow margin of 24%. And now for our outlook for the fourth quarter and the fiscal year 2025. First, our guidance philosophy overall remains unchanged. As a reminder, we base our guidance on trends observed in recent months and imply conservatism on these growth trends. So for the fourth quarter, we expect Revenue to be in the range of $912 to $916 million, which represents a 24% year-over-year growth. Non-GAAP operating income is expected to be in the range of $216 to $220 million, which implies an operating margin of 24%. Non-GAAP net income per share is expected to be in the range of 54 to 56 cents per share, based on approximately 367 million weighted average diluted shares outstanding. And for the full year, fiscal year 2025, we expect revenues to be in the range of 3.386 to 3.390 billion dollars, which represents 26% year-over-year growth. Non-GAAP operating income is expected to be in the range of 754 to $758 million, which implies an operating margin of 22%. And non-GAAP net income per share is expected to be in the range of $2 to $2.02 per share, based on 364 million weighted average diluted shares. And finally, some additional notes on our guidance. We expect net interest and other income for the fiscal year 2025. to be approximately $170 million. We continue to expect cash taxes in 2025 to be about $10 to $20 million, and we continue to apply a 21% non-GAAP tax rate for 2025 and going forward. And finally, we expect capital expenditures and capitalized software together to be 4% of revenues in fiscal year 2025. To summarize, we are pleased with our execution in Q3. We are well positioned to help our existing and prospective customers with their cloud migration and digital transformation journeys, including their adoption of AI. And I want to thank Datadogs worldwide for their efforts. And with that, we'll open the call for questions. Operator, let's begin the Q&A.

Thank you. At this time, we'll conduct the question and answer session. As a reminder to ask a question, you'll need to press star 11 on your telephone and wait for your name to be announced. To withdraw your question, please press star 11 again. Please stand by while we compile the Q&A roster. And our first question comes from the line of Cash Ryan of Goldman Sachs. Your line is now open.

Hi, thank you very much. I appreciate it. Congratulations on the spectacular results and the showing of sequential improvement across the board. Olivia, I had a question for you. We've talked about GPU monetization versus CPU monetization. So how closer are we to the point where you can confidently expand and get your share of the customer wallet when it comes to whether it's training workload, inferencing workload on the GPU clusters, which are becoming more prevalent and increasingly larger part of the compute build out in the future. That's it for me. Thank you so much.

So we have products that are getting into the market now for GPU monitoring, but these don't generate any significant revenue yet. So all the revenues we share, like the acceleration, et cetera, that's not related to us capitalizing more on GPUs. That's a future opportunity.

Thank you. One moment for our next question. Our next question comes from the line of Sanjit Singh of Morgan Stanley. Your line is now open.

Yeah, thank you for taking the questions and congrats on the acceleration in growth this quarter. Olivia, I wanted to talk about some of those enterprise trends you're seeing in sort of your non-AI cohort. What do you sort of put the improved performance and growth this quarter on? You mentioned that the sales productivity or the benefits from some of the sales investments is starting to come online. Is there sort of an uplift in sort of the cloud migration trends? Are you starting to see enterprise build more AI applications? I'd just love to get your perspective on the underlying trends in the enterprise and the mid-market business.

Yeah, I'd say there's three parts to it. One part is the demand environment is positive in general. I don't know that we see massive acceleration of cloud migration, but at least the environment is not a pushing the other way. We know which happens from time to time. That's point number one. Point number two is we've been growing sales capacity quite a bit and we've created new go-to-market motions to grow up to the kind of customers we were not getting before. We've done quite a bit of investment over the past couple of years and we see that starting to pay off. As I said also, we feel good about the the Q4 in terms of pipeline on the sales side. So it's too early to tell yet. We still have to close the deal. But we feel good about the scaling of our go-to market. And point number three is we have a number of products that we've been developing over the years, some of them early, some of them a little bit further along. that are really clicking. You know, we see, you know, we have a lot of success with getting larger crises to adopt flex logs, for example. We have a lot of success with some of the new products, products such as for analytics that we mentioned on the call. We're seeing some large land deals with our cloud team, you know, so all of that is contributing to the picture you're seeing today.

And just as a follow-up on the AI observability opportunity, when you look at some of the independent software vendors that are releasing agentic solutions, agentic portfolios, a number of them are including observability as part of their value proposition. Is there any work you think Datadog has to do to sort of infiltrate that market or make sure that customers look to Datadog as that agentic monitoring capability as some of these independent software vendors try to bundle in observability into their solutions. I'd love to get your perspective on that.

Yeah, I mean, there's absolutely no doubt to us that the customers will need and want a unified platform for observability for all of these. There's two parts to that. One is Historically, every single piece of software we integrate with, whether that's SaaS or things that customers run themselves, also has its own management console and observability console. But you're not going to log into 70 or in the case of customers we mentioned, they use 60 integrations for the smaller customers, 150 integrations for the larger ones. It's not practical to actually go and manage that separately. So we think all of that belongs in a central place. And that's the historical trend we've seen. We also think that you can't separate the AI parts from the non-AI parts of the business. So, you know, you're not going to look at your agent separately that you do at your, you know, web hosting and your database and your, you know, everything else you have in your stack. So all of that in the end will be attached to observability.

Very clear. Thank you very much.

Thank you. One moment for our next question. Our next question comes from the line of Raymond Lenchao of Barclays. Your line is now open.

Perfect. Congrats for me as well. That sounded like an amazing quarter and nice to see it coming together. On the AI side, and I don't want to talk about the big customer, but more the other ones, like 15 customers over 1 million, that's like a big number and 100 over 100,000. How do I have to think about the nature of those? Are those kind of especially the bigger ones, those kind of model builders, but then even 15 is a big number, and over 100 sounds like this whole new application world that we've all been kind of waiting for starting to come together. Is that kind of what's going on there? Because it does sound quite exciting and much more broader than we thought. Thank you.

It's actually fairly broad. So there is model vendors, there's models that can be that can be video, it can be sound generation, it can be all of the various parts of the stack you see as independent companies. It can be quite a few companies that work on the coding side, so coding assistants and vibe coders and everything in that range. Some of these are very new companies, some of these are not very new companies. Some of these started five, seven, eight years ago and We're sort of not necessarily AI native from day one, but very quickly that would give them the growth they see today with the people to AI. So we share a bit of that. We have companies that are all the parts of the stack in AI, you know, on the, say, the serving side, the other components of the infrastructure. And we have other companies that are more purely applications filled with AI. So we have a bit of everything in there. It's actually fairly representative of the space.

Okay, perfect. That's exciting. Thank you.

Thank you. One moment for our next question. Our next question comes from the line of Mark Murphy of J.P. Morgan. Your line is now open.

Oh, thank you so much. You had mentioned the expansion of the contract with your largest AI native customer, and I believe you said better economics for a higher commitment. Can you speak to that? Because I would assume a higher commitment would carry a volume-based discount. I'm just trying to understand if, for some reason, if that was not the case here, what did you mean by better economics? And then I have a quick follow-up.

Yeah, yeah. I mean, this is... without getting to the detail of any specific customer, the motion is always the same. Customers grow, they commit to more, they get better prices. So you see, again, talking about customers in general, you see growth of usage, drops in revenue as customers renew and get a higher commit and a better price, and then usually growth after that for those customers. That's the motion. that we've had with about 30,000 customers so far.

Okay. So the better economics part of it is just where it's going to be netting out like 12 months down the road? Is that what you mean?

Well, the better economics means, you know, you're coming tomorrow, you get a better price, you know. And as we remember, we have a usage model. So we charge people every month on what they use at the price we agreed. So if you get better economics, and your usage is somewhat similar month-to-month, or month-to-month to pay less. But the overall backdrop of our business is increased consumption.

Okay, and then as a quick follow-up, Olivier, the acceleration that you saw in security growth is pretty noticeable, too. We recall, I think, about six months ago, you had ramped up and engaged a lot more with channel partners, which is a key ingredient to grow in a security business. Is it a function of that or is there a mindset change happening out there where customers want observability to be the central point of collection so that all the security teams and the ops teams are working with the same set of metrics and logs and traces?

Look, I think it's a number of things. Definitely, we've been investing in the channel and that's certainly helpful to the CPD business as a whole. The big win we mentioned on security, that we mentioned a couple of win in the cloud theme, these tend to be more related to product maturity, the strength of our underlying platform, especially when it comes to technology like FlexLogs, for example, and the fact also that we've been learning how to properly go to market for security, and I think we've been clicking in a way that's very exciting. Thank you.

Thank you. One moment for our next question. Our next question comes from the line of , your line is now open.

Good morning. Thank you for taking my questions. Ali, I'll start with you and have a follow-up for Dave. On the on-call product, Ali, how do agentic advancements in general detract or enhance the value proposition here? And I'm very simplistically thinking about the the core nature and value proposition of the OnCall product intelligently routing requests for remediation, right? So how do you just broader advancements in AI help beef up and or detract your ability to monetize this product? And then just to follow up for David, please.

Well, I mean, look, if you zoom out, we entered the field with OnCall because we wanted to own the end-to-end incident resolution. So we wanted, because before that we were detecting the incidents and sending the alerts, and then we were pretty much where the resolution happened after that, you know, customers were spending their time in data to diagnose and understand what was going on. So we wanted to own the full cycle. And we thought that with AI in particular, we'd have the ability to do things. If we might, if we are on the whole cycle that we couldn't, we couldn't do otherwise. What you see right now is this resonance with customers. They're adopting the product. We've mentioned some exciting customers with one with 5,000 seats for Encore, which is very exciting. But in the future, there's many more things we can do and working on for that product. If we both detect the incident and notify, we can do some sort of things such as even predicting the incident and notifying early or re-routing early or, you know, or telling people before the incident actually takes place, you know, how they can potentially fix it. So these are all things we're working on. I mean, look, if you look at the various product announcements we've made, whether that's BCI, SRE, or the time series forecasting model we've released, when you assemble all that, you get to a very, very interesting picture of what we can do in the future. So we're excited about that. Our customers are excited about the vision there, too, and that's why these products are successful.

Appreciate that. David, on net retention rates, why aren't we necessarily seeing more upward pressure on the metric, just given the strength of expansionary bookings that you alluded to in the quarter from the install base? And I mean, I suspect it's because it's a trailing 12-month metric, but any directional color you can just share on that and any high-level commentary on some of the non-AI native net retention rate trend behavior. Thank you.

Yeah, you've nailed it. It's a trailing 12 months. It's a number that's rounded. It has the dynamics that you might expect in that the growth of the non-AI natives has been, as we mentioned, a combination of landing and expanding at higher rates than we've seen in recent quarters. So if that continues as you go into a trailing 12-month metric, you see a directional movement.

Thank you. Thank you. One moment for our next question. Our next question is from the line of Eric Heath of KeyBank. Your line is now open.

Hey, great. Thanks for taking the question. Ollie, David, Bits.ai seemed like a really exciting thing out of Dash. And I know it's still in preview, but you mentioned there's a lot of interest there. So I'm just curious how you think about the agentic opportunity with Bits.ai and how meaningful this can be for 2026 as a differentiator versus competition and also as a revenue contributor. Thanks.

Yeah. So it, I mean, look, it's, it's super exciting. The feedback's very good on it. The, I mean, we've been collecting all the, so I read one quote, um, but you know, we have, you know, dozens that look just like that, that was sent to us by customers. Um, and so that's very, very exciting. The, We also started having some customers buy and come to it just to show value and to make sure we were on to the right product mix. And so we feel good that this is something that is high quality and we can monetize. In terms of the impact for next year, on the packaging side, I'm not completely sure yet whether the biggest impact will be seen from what we charge for Bits.ai itself or for the rest of the platform that it gets benefits from the differentiation of Bits.ai's. I think that's more of a broader question of packaging and monetization of AI. And remember that we have a product that is usage-based, so anything that drives usage up and adoption from customers is good for us and is very, very monetizable. But what we can tell is this is differentiating. This is good. It works significantly better than anything else we've heard of in the market. And we're doubling down on it. We have many, many teams now working on Deepening Bits AI, sorry, so making sure it goes further into the resolution, doesn't just point to the issue but fixes the code, all these kind of things, working hard on that. We're also working on breadth, you know, making sure that we train it on many more types of data, many types of sources, sometimes even systems that are, systems that are not Datadog, you know, so we can cut across to other systems our customers are using. So we're very, very aggressively developing Bits AI, sorry. It's resonating very well in the market.

Thank you. We'll move it for our next question. Our next question comes from the line of Gray Powell of BTIG. Your line is now open.

Oh, great. Thanks for taking the questions. And congratulations on the great results. So maybe just like taking a step back. If we go back to the beginning of the year, Datadog was expecting 19% revenue growth. it looks like you're tracking to something over 26% growth now, and that's just the high end of your guidance. So I guess my question is, what surprised you the most this year? And then just how do you feel about the sustainability of those drivers as you look forward?

I mean, look, so first, I apologize for already agreeing on the results. We might do it again, but we'll see. I think the biggest surprise uh for us has been that the so ai in general has uh or ai adoption has gone faster than we thought it would uh at the beginning of the year so we've seen that across our ai cohort we've seen also that we we got some of our new products and new uh like the changes we are making on the go to market side to click perhaps earlier than uh we would have thought otherwise um so all you know you know We saw the leading part of the business with AI grow faster, not the lagging, but the slower growing, more traditional property business also accelerate, and that gives us where we are today.

And I'd add, we have a good demand environment, and we've been investing, whether it be in the products that Ali's been talking about or in the sales capacity. We made clear that we were an investment, and we're seeing those investments pay off.

All right, that's helpful. Thank you. Thank you. We'll move it for the next question. Our next question comes from the line of Koji Akita of Bank of America Securities. Your line is now open.

Yeah, hey, guys. Thanks so much for taking the question. Just one for me here. I wanted to ask a question on the inflection and the non-AI native growth and how to think about the areas of strength in this cohort. Is it coming from your largest enterprises? Is it coming from a certain type of customer? Is there a common theme in the workloads that you're seeing or the products that are being added on that is driving that strength? Or is it just really just broad-based? What I'm trying to get at here is I'm really trying to understand more the durability of this growth reflection. Thank you.

So it is broad-based. And I think, again, it speaks to a couple of things. It speaks to the fact that, in general, the demand environment is good. Though I would say there's been a very, very high growth of hyperscaler revenue over the past, max acceleration for the hyperscalers in general. A lot of that is GPU-related, but the growth we're seeing here and the acceleration we're seeing here is largely not GPU-related. There's a little bit of it, but not a ton of it. So that's not exactly what you've seen with some of the other vendors there. One reason this is broad-based is these are the same products we sell to all customers, and this is largely the same go-to-market organization that we have a few segments, and we've been doing well at executing there. I think we've invested quite a bit in product, and we will keep doing it, and we see the results of that.

Yeah, I'll add that it's across the customer-based enterprise SMB. And when we look at it, it's not just an AI SMB. If you remove those AI companies, you still see a strengthening SMB demand cycle going on. And unlike in previous periods, it also is across spending ranges. We're not seeing larger spenders or smaller spenders. We're just seeing a broad trend of improved demand across the spending trends.

Remember, for us, SMB is any company of less than 1,000 employees. It includes a lot of very legitimate and growing businesses. You know, it's not just 10,000.

Thank you. Thank you. One moment for our next question. Our next question comes from the line of Itai Kettering of Oppenheimer & Co. Your line is now open.

Thanks and congrats, guys. Really great numbers. Ollie, in your answer to one of the questions and kind of going into the drivers behind the upside, you talked about sales capacity increase. You did talk a bunch about sales efficiencies. Is there a way you can give us some color on where you stand on percent of salespeople that are hitting quota? Where does that ratio stand relative to historical patterns for you guys? And as you approach 26th year, do you anticipate any material changes in the comp structure just given the breadth of product and their list of opportunities? How do you get people focused?

Yeah. So we feel good about the sales productivity in general. And the rule generally is You grow by scaling capacity and maintaining productivity. It's hard to drive both up at the same time. And remember, if you want to grow to 10x, you can do that by scaling it. You can't really do it by improving productivity, so you have to scale. And we've been doing that, and we've been successful at it so far. In terms of the compliance, look, we keep changing the way we compensate and the way we manage the sales force in general to make sure we have the right focus. One of the gifts of a business like ours is that we have a very heavy land mix pan model, and so we get a lot of growth from reaching customers. The challenge it creates on the other hand is, how do we get to focus the sales force on the newer customers, the smaller ones, and the new ones because it is more work to get an extra dollar for a smaller customer or for a new one than it is for an existing one that already has scale. And so a lot of the tweaks we make to our own plans relate to that. We make sure we direct our attention and we reward people for what is going to generate the most long-term growth for us. And we've made a number of changes. I won't go through them. These are internal changes. But with a number of changes this year, we see a number of them pay off. Another thing I mentioned on the call was we mentioned the win for one of our new go-to-market motions, and that's specifically getting in place multi-year plans to go after some larger customers that are tougher to lend than what we've done in the past. And sometimes it takes more than a year to lend certain types of customers. And the problem is if you can't plan only has a one-year horizon, like it doesn't give a great incentive for the sales force to go after those customers. And so we cordoned off a few of those companies who have special plans to go after that, and we're starting to see success with that, too. This is just an example. Appreciate it.

Thank you. We'll move in for our next question. Our next question comes from the line of Andrew Sherman of TD County, and it's now open.

Oh, great. Thank you, and congrats. I know you have a team focused on the Fortune 500, where there's still a lot of white space for you. Curious to hear how that team's ramping to productivity. Did that help drive some of the strong new logo bookings, and can this contribute even more next year? Thanks.

Yeah, I mean, look, and the team's not new, right? I mean, we've been focusing on that for many years, and we're tracking well. One thing I was mentioning just before was, One challenge even in the Fortune 500 is to make sure that we focus on landing new customers, you know, and make sure that there's the right amount of sales attention and reward for, you know, landing a customer, even if it's for a small amount. And I think we've done well. I mean, again, we can comment on that again after the next quarter when we have a full year of our new clients that have been validated. But so far, we feel very good about it.

Thank you. One moment for our next question. Our next question comes from the line of Alex Vulcan of Wolf Research. Your line is now open.

Yeah. Hey, guys. Thanks for taking my question, and congrats on dropping some truly inspiring quotes in the script. Maybe, Ali, one for you, and then I have a quick follow-up for David. Just the duration of this acceleration of the non-AI cohort. It seems like from all your forward-looking metrics, whether it's Billings, RPO, CRPO, those were, again, really, really strong. How long do you think we should think about the duration of this trend of this non-AI acceleration?

Well, you know, we're a consumption business, so the hardest thing to understand is what the future is going to look like for consumption. The way I would say it is we feel very good about it at the mid-term, long-term. Now, it hasn't slowed in even a month or quarter. That's harder to tell. And again, that's what we've seen through the life of the company. What we're still very confident about, though, is the motion in general for digital transformation and cloud migration is steady. Sometimes, you know, it slows down a little bit, but it reaccelerates after that. And we see that going on for a very long time.

And then maybe, David, for you, you know, look, gross profit dollar acceleration while you're seeing your largest customer, you know, kind of get. better unit economics is is also inspiring to see how should we think about the progression of gross margins and gross profit dollar growth particularly as you continue to also see the ai cohort acceleration yeah there's a couple things i think we've mentioned that you know we've been uh focused and have focused over the many years on the efficiency of our cloud platform we have significant engineering efforts around

cost of sales and delivery of value. And so we've been able to deliver on that. We also have a very broad customer base of, you know, distributed in terms of volumes. So as customers get larger and maybe get volume discounts, we have a number, you know, a lot of customers coming in at smaller. So that balance there. And then, and then in terms of, of, of, the sort of the future repeat what we've always said that we've been running the company with a gross margin plus or minus 80 you know we've given that range and not changed it and we watch it and it gives us signals in terms of efficiency how we're operating it gives us single signals in pricing and things like that and wouldn't change the comments we made over the many years about the

looking at that and then you know developing operations and strategies around that perfect thank you guys yep thank you one moment for next question our next question comes online of ryan mcwilliams of wealth fargo your line is now open hey thanks for taking the question just one for me

On the large AI contract expansion that you provided commentary on, is there any way we can think about the contribution change from this customer over the next few quarters?

Thanks. No, I mean, we don't provide that kind of information on individual customers. We're trying to give a picture of the overall business. Generally, I think as Ali mentioned, on our larger customers, we have a motion of the expansion of volume, and then we work on the term and the volume-based pricing, but we don't give guidance like that on individual customers. Fair enough.

Thank you. One moment for our next question. Our next question goes in light of Mike Sickles of NeedM. Your line is now open.

Great. Thanks for taking the questions, guys. I just wanted to come back to it, Ali. For the non-AI native strength, I know we've kind of hit on this a number of times, whether it's roadmap, sales capacity, execution, but kudos on the numbers here. I'm just trying to get a better sense of the why now. Is it just a composite of all those different pieces clicking together this quarter, or is there anything more to unpack there? And then I have a follow-up for David.

Again, I don't think there's a lot more to it back there. And I know it's boring in a way, but it's also the way we've been growing for the past 15 years of the week. So that's, I would call it the usual.

Awesome. Awesome to hear. Okay. And for the follow-up to David, David, I don't want to take anything away from the Q3 results you guys just posted. And we obviously have the strong guide here for Q4. But I just can imagine myself a month from now starting to get inbounds from certain folks asking about the holiday season and the fact that we have the holidays landing on weekdays in Q4 here. Can you just kind of discuss how you thought about constructing guidance for this Q4 year?

Yeah, we have years of experience of analyzing the day by day patterns. In the holidays, we know that the holiday period ends up in the usage side because of vacation holidays. And we incorporate that into our guidance. We're, I think, involved a lot over the years in sort of days adjusted, types of days, et cetera. And so we would be incorporating that like we've incorporated in other years. If there are differences in this calendar period, we incorporate that as always.

Very helpful. Thank you, guys.

Thank you. One moment for our next question. Our next question comes from the line of Carl Kersted of UPS. Your line is now open.

Okay, great. Thank you. I'll ask one for David and one for Olivier. David, first of all, congratulations on the extension of the larger contract. I think everybody on the line is applauding that. I know you're reticent to get into any details, but maybe I could try. Are you able to clarify whether that was a one-year deal or multi-year? And then related to that, David, what is the contribution to CRPO from that deal, which I presume landed in your CRPO number? If it is a one-year deal, does the entirety of that contract contribute to the sequential CRPO performance in the quarter? So that's it for you, David. And then, Olivier, maybe I'll just ask both at once. Some of the very large AI natives are beginning to diversify to utilizing Oracle's OCI and Stargate. And I'm wondering, what's the opportunity for Datadog to essentially follow that behavior and begin scaling on Oracle, Stargate, or because a lot of what Oracle is doing with the AI natives is training clusters, perhaps that near-term opportunity is more limited. Thank you both.

Yeah, on the first point, I think, you know, we give a lot of examples and, you know, our motion, which our customers would be following, including that one, would be we fix out annual plus commits. We're not commenting on individual contracts here, but it would follow a typical path to other types of contracts. So that's what we would do.

Yeah, and on OCI, look, we've built an OCI integration, and we see more demand from customers on OCI. Some of the things we see, like the targets, et cetera, these are extremely custom-built apps. I don't know, they're not necessarily exactly cloud, because they're custom-built for specific customers. So the opportunity there is more remote today, but it's, again, One company is that it's not a fantastic opportunity to productize, but if 10, 15, 20, 50 companies start using that, then that really becomes a commercial opportunity. And so we very much plug into all of that, and we go basically where our customers are.

I think you mentioned about the RPO. No, I think in this case, we've mentioned this current and the And the total is roughly the same. And there wouldn't be anything in that contract that would have been, you know, materially around those numbers. Those numbers, I think we mentioned, are produced from the bookings growth more generally and not from that particular contract.

Okay. Thank you.

Thank you. One moment for our next question. Our next question comes from the line of Jake Roberge of William Blair. Your line is now open.

Yeah, thanks for taking the question. Just on the recent go-to-market investments, obviously seems like there's been a lot of traction thus far with those. So I'm curious if there are any areas like security or the new logos or upmarket that you could look to lean even deeper into, just given the growth that you've seen here.

Yes, definitely. I guess some things we we didn't do it this year that we were definitely going to do next year. So there's a number of things. We're in Q4, right? So we're in the middle of planning for next year. And we basically will keep scaling what's working, stop doing some of the things that are not conclusive, and then try a few more things. That's the way it works. Interestingly enough, building your go-to market is not that different from building software. You experiment, you gather data, you see what's working, what's not working, and you build a system.

That's helpful. And then just on the new BITS AI agents, can you just talk about the early feedback that you've gotten for those solutions and maybe how the engagement with those agents has compared to kind of the ramp of security flex logs? I know obviously much earlier days, but just how it compared when those were still largely in the preview phase.

I mean, look, the DCISR agent really has a role factor for customers. So what works really well is, and we've seen that in a lot of times, we set it up for them, it's running on their alerts, and they go through an outage, and they still go through the motions. So they still set up a bridge, and they have 20 people, and they spend two hours, and in the end, they have an idea of what went wrong. And then they go to that and they see, oh, well, there's an investigation that had run. And three minutes into the update, it got the same conclusion that was up two hours later with 20 people on the call. And that completely eye-opening for customers when they see that. So that's why we get many quotes about it So now, you know, there's more we need to do there. Like, you know, customers say, oh, this is great. Now, can you make this for me? Can you do this? Can you do that? Can you support that other system that right now you can't actually set it up for? So we have a very, very full roadmap of things we need to do, and we're doubling down. We also shipped, I mean, this one is in preview, but we shipped a security agent that looks at vulnerabilities and looks at security signals. and those triage that basically look at trying to investigate what might be benign or what might be a real issue. We also are getting very, very positive feedback for that. And in fact, that's what helped us win some large land deals for our cloud theme products, you know, because the combination of the theme that runs extremely efficiently on top of the observability data that runs very efficiently on top of FlexLog, but also saves an immense amount of time by getting, you know, 90% of the issues out of the way with automated investigations. That's extremely attractive to customers. All right, and I think with that, we're going to close the call. So before we go, I just want to give one quick shout out to the team, because I know, as I said earlier, we have quite a lot going on in Q4, whether it's on the planning side, on the product building side, or on the sales side, where I said we have a really, really exciting pipeline So we have a lot to do. I want to thank the team for the hard work there. Also, I'm looking forward to meeting a lot of our existing and new customers at AWS reInvent in a few weeks. And I'll see you all there. Thank you all.

Thank you for your participation in today's conference. This does conclude the program. You may now disconnect.