MongoDB, Inc. (MDB) Q3 2026 Earnings Call Transcript

Good day, and thank you for standing by. Welcome to the MongoDB's Third Quarter Fiscal Year 2026 Earnings Conference Call. Please be advised that today's conference is being recorded. I would now like to turn the conference over to your speaker for today, Jess Lubert, VP of Investor Relations. Please go ahead.

Thank you, operator. Good afternoon, and thank you for joining us today to review MongoDB's third quarter fiscal 2026 Financial Results, which we announced in our press release issued after the close of market today. Joining me on the call today are CJ Desai, President and CEO of MongoDB; and Mike Berry, CFO of MongoDB. Following our prepared remarks, Dev Ittycheria, MongoDB's former President and CEO and current member of the Board will join us for Q&A. During this call, we will make forward-looking statements, including statements related to our market and future growth opportunities. Our opportunity to win new business, our expectations regarding Atlas consumption growth, the impact of non-Atlas business and multiyear license revenue, the long-term opportunity of AI, our financial guidance, and underlying assumptions and our investments and growth opportunities in AI. These statements are subject to a variety of risks and uncertainties, including the results of operations and financial conditions that could cause actual results to differ materially from our expectations. For a discussion of material risks and uncertainties that could affect our actual results, please refer to the risks described in our quarterly report on Form 10-Q for the quarter ended July 31, 2025, filed with the SEC on August 27, 2025. Any forward-looking statements made on this call reflect our views only as of today, and we undertake no obligation to update them except as required by law. Additionally, we will discuss non-GAAP financial measures on this conference call. Please refer to the tables in our earnings release on the Investor Relations portion of our website for a reconciliation of these measures to the most directly comparable GAAP financial measures. With that, I'd like to turn the call over to CJ.

Thank you, Jess, and thank you to everyone for joining. I'm honored and genuinely excited to speak with you as the CEO of MongoDB. This is an incredible company and stepping into this role is a privilege. I want to start by thanking our customers, partners, and employees for everything you have done to build MongoDB into what it is today. I especially want to acknowledge Dev whose leadership and vision created a phenomenal company, which has strong momentum and a tremendous market opportunity ahead. Many have asked why I chose MongoDB; I had multiple opportunities to lead other technology companies, but MongoDB stood apart. We are at a true inflection point driven by major shifts across cloud, data, and AI. MongoDB has the potential to become the generational modern data platform of this evolving era, an opportunity that comes once in a lifetime. I am a truly customer-obsessed leader. So during my diligence, I spoke with multiple customers. Across these conversations, the message was clear: MongoDB already powers core, mission-critical workloads for enterprises that are modernizing their technology stack. At the same time, MongoDB is uniquely positioned at the center of the AI platform shift. Few technology companies have that combination of durable core strength and emerging platform relevance. Throughout my career, I have driven product to platform transformation at some of the most respected technology companies. Looking at MongoDB today, I see all the ingredients needed to build an iconic modern data platform company. World-class technology, a strong innovation engine, deep developer and customer pool, and exceptional talent. We have everything required to become the generational data platform of choice in the AI era. Now onto this quarter's results. Atlas performance was strong, accelerating to 30% year-over-year growth, up from 29% in Q2 and 26% in Q1. We generated total revenue of $628.3 million, up 19% year-over-year and above the high end of our guidance, driven by strength in Atlas. We delivered non-GAAP operating income of $123.1 million or a 20% non-GAAP operating margin. We ended the quarter with over 62,500 customers adding 2,600 in the quarter and 8,000 year-to-date, reflecting 65% growth in customer additions on a year-to-date basis driven by the strong performance of our self-serve motion. Q3 was an exceptional quarter that was driven by our continued go-to-market execution and the broad-based demand we are seeing across the business. At the same time, we significantly outperformed on operating margin, demonstrating that we can drive durable revenue growth while simultaneously expanding profitability. Now let me explain why I see such a large opportunity ahead for both core operational data and emerging AI workloads. Our core business is strong across self-served and enterprise customers even before any AI tailwinds. In my first 3 weeks, I've met with over 30 customers from AI-native companies to C-suite technology leaders at Fortune 500 companies. Those conversations have only strengthened my conviction in MongoDB's opportunity. Customers already depend on us for mission-critical workloads today, and they are leaning in even further, betting on MongoDB to power the AI applications that will shape their future. The expansion opportunity in front of us is immense. We already serve more than 70% of the Fortune 100, and many of the world's largest banks, health care organizations, and manufacturers run their mission-critical workloads on MongoDB. Even with this foundation, there is still significant room to broaden our footprint within the enterprise. A strong example of this expansion opportunity is a major global insurance provider that has adopted MongoDB broadly across its enterprise. The company selected MongoDB Atlas to modernize several mission-critical systems, including its next-generation policy administration platform, analytics rating engine, unstructured data repositories, and hundreds of supporting services. Since moving its policy platform to Atlas, the insurer has expanded from just a small set of regions to nationwide and significantly accelerated the rollout of new products and distribution channels. Standardizing on Atlas has given the organization the scalability and reliability to improve customer experience, support more advanced data and AI capabilities, and increase development velocity, all central to its transformation and growth ambitions. All of this momentum in the core business is happening before the AI wave has meaningfully impacted our results. We are still early, but the signs are encouraging from AI-native start-ups building intelligent applications on MongoDB to large enterprises developing AI agents that will reshape how they operate. AI applications must connect what large language models know with what companies know, which is their proprietary data, systems, and real-time context. This is fundamentally an information retrieval problem, and it requires a very different architecture than the last generation of software. Rapidly evolving AI models uncover new complex properties about entities, and rigid tabular stores cannot deliver the real-time high accuracy performance that AI systems require. At the same time, AI is dramatically increasing the speed at which applications are built and iterated, and fixed database schemas simply cannot keep pace. This is where MongoDB has a structural advantage. Our document model, natively, JSON is built for diverse class-changing and interdependent data. Our integrated search, vector search, and Voyage embeddings remove the need for brittle bolt-ons, and we are seeing industry-leading results. Number one, on the Hugging Face retrieval embedding benchmark with Voyage MongoDB models and the #1 vector database on DB engines. Advances in our embedding and reranking models drive meaningful accuracy gains, enabling AI applications to deliver more grounded responses with fewer LLM hallucinations while lowering storage costs and query costs through smaller, more efficient embeddings. Because all of this is delivered in a unified platform that runs anywhere, customers can keep operational and AI workloads together, simplify their architecture, and innovate faster. As AI adoption accelerates, MongoDB is positioned not just to participate in the wave, but to help define it. We are already beginning to see this play out with AI-native customers like Mercor, which is redefining hiring with its fully automated platform that uses AI to assess and match talent with the opportunities they are best suited for. Mercor uses MongoDB Atlas to store the AI data behind its platform that directly connects professionals to AI model training and evaluation roles. Originally a self-serve customer, the company is also utilizing Voyage embeddings and Atlas Vector Search. Atlas has the scale to support Mercor's 50% month-over-month growth, allowing the company to keep its software engineering team lean and agile as it expands to over $10 billion in value. This is just one example of how customers are building AI-native applications and companies on MongoDB. We are also seeing meaningful traction among large enterprises that are starting to build AI applications that have a material impact on their business. For example, a highly influential global media company aims to increase engagement via enhanced content recommendation for its vast repository of multimodal assets across its 70-plus websites. Their existing stack powered by Elasticsearch hit a performance wall struggling with the complexity of new embedding models. Recognizing that rigid systems stifle innovation, the engineering team re-architected on MongoDB Atlas and MongoDB Atlas Vector Search. Working with MongoDB experts to deliver a proof of concept in just weeks, they integrated Voyage AI models directly alongside their data. The solution scaled effortlessly, cutting latency by 90% and reducing operational spend by 65%, driving a 35% increase in click-through rates, ultimately providing millions of global readers with a seamless, deeply personalized discovery journey. The bottom line is that the business is performing exceptionally well. Existing customers are expanding with us and net new customer additions continue to show strength. Companies in nearly every industry and across every geography are choosing MongoDB because we deliver the features, performance, cost-effectiveness, and AI readiness they need in a single data platform. Given the continued robust performance of Atlas, along with the healthy underlying fundamentals we are seeing in the business, we are raising our financial guidance for the fourth quarter and the full fiscal year 2026 and reiterating our commitment to the long-term financial model outlined at our recent Investor Day. Over the next few months, my focus is straightforward. Deepening customer relationships, advancing our innovation agenda as we build the generational modern data platform for the multi-cloud and AI era, scaling our go-to-market efforts, and supporting our people so they can do their best work. I believe MongoDB is a company that has only begun to realize its vast potential and I look forward to unlocking this potential in the years to come. With that, I'll now hand the call over to Mike to discuss the financial results and outlook in greater detail. Mike?

Thank you, CJ. I want to extend a big welcome to you from all of the employees at MongoDB. We are excited to have you join the team. I look forward to working with you to continue to execute on our business plans and drive meaningful shareholder value. I also want to thank Dev for the partnership and our time working together. I believe we accomplished a lot in a short period of time and appreciate all of your guidance and leadership. Best of luck in the next stage of your life journey. Okay. Now let's move on to the financial results. I will begin with a detailed review of our third quarter results and then finish with our outlook for the fourth quarter and fiscal '26. I will be discussing our results on a non-GAAP basis unless otherwise noted. As CJ mentioned, we had another strong quarter as we exceeded all of our guidance ranges and are increasing our full year outlook across the board. In the third quarter, total revenue was $628.3 million, up 19% year-over-year and above the high end of our guidance. Shifting to our product mix. Atlas revenue outperformed our expectations as year-over-year growth accelerated to 30% in the third quarter and now represents 75% of total revenue. This compares to 68% of total revenue in the third quarter of fiscal '25 and 74% last quarter. In the third quarter, Atlas consumption growth was relatively consistent with last year's growth rates, which drove the acceleration in revenue as well as growth in absolute revenue dollars for the third straight quarter. Atlas growth was driven by continued strength with our largest customers in the U.S. and broad-based strength in EMEA. This strength is being driven both by new workloads and growth of existing workloads. We believe these dynamics reflect our growing strategic importance to many customers and our ability to win more critical workloads due to the strength of Atlas. You can see that progress in our total company net ARR expansion rate, which increased to 120% in the third quarter, up from 119% last quarter. Turning to non-Atlas. Revenue came in ahead of our expectations in the quarter as we continue to have success expanding within our existing non-Atlas customer base. Non-Atlas ARR, which reflects the underlying revenue growth of this product without the impact of changes in duration grew 8% year-over-year. We continue to see consistent trends in non-Atlas in the third quarter, which reflects the desire of some of our largest customers to build with MongoDB long term for their most mission-critical applications. We also benefited from higher-than-expected multiyear revenue in the third quarter as approximately two-thirds of the non-Atlas revenue outperformance versus the high end of guidance was attributable to multiyear outperformance. We had another strong quarter for customer adds as we grew our customer base by approximately 2,600 sequentially, bringing the total customer count to over 62,500, which is up from over 52,600 in the year-ago period. The growth in our total customer count is being driven primarily by Atlas, which had over 60,800 customers at the end of the third quarter compared to over 51,100 in the year-ago period. We ended the quarter with 2,694 customers with at least $100,000 in ARR, representing 16% growth versus the year-ago period. Moving down the income statement. Gross profit for the third quarter was $466 million, representing a gross margin of 74%, which is down from 77% in the year-ago period. Our year-over-year gross margin decline is primarily driven by Atlas growing as a percent of the overall business. Although Atlas gross margins are slightly below the total company gross margins, they continue to improve year-over-year. Our income from operations was $123 million for a 20% operating margin compared to 19% in the year-ago period. We are very pleased with our stronger-than-expected operating margin results, which benefited from both our revenue outperformance and lower-than-expected operating expenses. Net income in the third quarter was $115 million or $1.32 per share based on 86.9 million diluted shares outstanding. This compares to net income of $98 million or $1.16 per share on 84.2 million diluted shares outstanding in the year-ago period. Turning to the balance sheet and cash flow. We ended the third quarter with $2.3 billion in cash, cash equivalents, short-term investments, and restricted cash. During the quarter, we spent $145 million to repurchase approximately 514,000 shares which was executed under our previously announced $1 billion total share repurchase authorization. Operating cash flow was well above our expectations at $144 million, and free cash flow was $140 million, which compares to $37 million and $35 million, respectively, in the year-ago period. Our cash flow results were driven primarily by strong operating profit and improving working capital dynamics, particularly related to higher cash collections. We remain confident in our ability to drive higher and more consistent free cash flow going forward. Before we go into our guidance for the rest of fiscal '26, let me recap some of the enhancements we have made to our approach to guidance since I joined MongoDB. Importantly, we are providing more visibility into our expectations for Atlas growth as well as non-Atlas ARR growth each quarter. That being said, we will continue to be prudent in our forecasting of multiyear deals and only include those deals where we have very clear visibility. Our goal is to give you a more transparent view into our expectations for the business and our approach to guiding the non-Atlas business. Now let me share some of the assumptions driving our outlook for the rest of fiscal '26. Number one, we are continuing to see strong momentum in Atlas, which has experienced relatively consistent consumption growth through the first three quarters of the year. And comparable seasonal patterns as compared to fiscal '25. We are seeing strength with existing customers, along with momentum in new accounts as customers large and small increasingly recognize the strategic value of Atlas. As a result, we now expect Atlas to see approximately 27% revenue growth in the fourth quarter of fiscal '26, which is higher than our previous expectations of growth in the mid-20% range. This outlook reflects our continued confidence in Atlas while taking into account the historical seasonal variability and consumption patterns during the holiday period. Number two, we continue to experience steady ARR growth in our non-Atlas business and have good line of sight to several large multiyear deals we either already have or expect to close in the fourth quarter of the year. Based on these dynamics, we now expect our non-Atlas business to grow in the upper single-digit percent range year-over-year in the fourth quarter. Number three, we continue to make strategic investments in engineering, marketing, and direct sales capacity to drive continued growth. Some of these planned investments have taken longer to implement than expected and have shifted into the fourth quarter of fiscal '26 and fiscal '27, which has benefited our operating margin during fiscal '26. Fourth, we continue to make progress on free cash flow conversion, which is now expected to exceed 100% for fiscal '26. Finally, we will continue to execute our share buyback program to help offset dilution from employee equity awards. In addition to our buyback, this past quarter, we began settling the taxes due on the vesting of employee RSUs with cash instead of issuing new shares. We also expect to receive over 1 million shares of stock for the cap calls associated with our 2026 notes that mature in January 2026. All of these actions will help us manage share count for the long term and illustrate our commitment to being good stewards of your capital. Now let's shift to guidance in the fourth quarter and fiscal '26. For the fourth quarter, we now expect revenue of $665 million to $670 million, which equates to 21% to 22% year-over-year growth. We expect non-GAAP income from operations to be in the range of $139 million to $143 million for an operating margin of approximately 21%. We expect non-GAAP net income per share to be in the range of $1.44 to $1.48 based on 86.5 million diluted shares outstanding. For fiscal '26, we now expect revenue to be in the range of $2.434 billion to $2.439 billion, an increase of $79 million from the high end of our prior guide and representing full-year revenue growth of 21% to 22%. We are raising our non-GAAP income from operation expectations by $109 million at the high end and are now targeting a range of $436.4 million to $440.4 million for an operating margin of approximately 18%. We expect non-GAAP net income per share to be in the range of $4.76 and to $4.80 based on 86.7 million diluted shares outstanding. Note that the non-GAAP net income per share guidance for the fourth quarter and fiscal '26 assumes a non-GAAP tax provision of 20%. While we will provide detailed guidance for fiscal '27 on our fourth quarter call, I would like to comment on how we are thinking about a few metrics as we sit here today. First, we remain committed to the long-term model presented at our Investor Day in September and continue to make great progress against all of the objectives highlighted at the event. We have seen strong margin expansion and free cash flow performance in fiscal '26. And both of these metrics are tracking well above the long-term targets we discussed in September. As we look ahead to fiscal '27, we will continue to make strategic investments to focus on driving growth going forward. With these planned investments and the timing of headcount adds, we continue to target 100 to 200 basis points of margin expansion on average and 80% to 100% for free cash flow conversion outlined in our long-term model. Second, our non-Atlas business is on track to exceed our prior expectations for fiscal '26 due to the stronger performance, including greater-than-expected large multiyear deals. Given this outperformance and our current bottoms-up forecast for fiscal '27, we currently do not expect non-Atlas multiyear transactions to provide either a meaningful headwind or tailwind to revenue in fiscal '27. To summarize, we had another very strong quarter. We are pleased with our ability to drive both revenue growth across the business while increasing our operating profit expectations and driving meaningful free cash flow. We remain incredibly excited about the opportunity ahead, and we will continue to invest responsibly to drive long-term shareholder value. With that, Lisa, we would now like to open the call up for questions.

Good day, and thank you for standing by. Welcome to the MongoDB's Third Quarter Fiscal Year 2026 Earnings Conference Call. Please be advised that today's conference is being recorded. I would now like to turn the conference over to your speaker for today, Jess Lubert, VP of Investor Relations. Please go ahead.

Thank you, operator. Good afternoon, and thank you for joining us today to review MongoDB's third quarter fiscal 2026 Financial Results, which we announced in our press release issued after the close of market today. Joining me on the call today are CJ Desai, President and CEO of MongoDB; and Mike Berry, CFO of MongoDB. Following our prepared remarks, Dev Ittycheria, MongoDB's former President and CEO and current member of the Board will join us for Q&A. During this call, we will make forward-looking statements, including statements related to our market and future growth opportunities. Our opportunity to win new business, our expectations regarding Atlas consumption growth, the impact of non-Atlas business and multiyear license revenue, the long-term opportunity of AI, our financial guidance, and underlying assumptions and our investments and growth opportunities in AI. These statements are subject to a variety of risks and uncertainties, including the results of operations and financial conditions that could cause actual results to differ materially from our expectations. For a discussion of material risks and uncertainties that could affect our actual results, please refer to the risks described in our quarterly report on Form 10-Q for the quarter ended July 31, 2025, filed with the SEC on August 27, 2025. Any forward-looking statements made on this call reflect our views only as of today, and we undertake no obligation to update them except as required by law. Additionally, we will discuss non-GAAP financial measures on this conference call. Please refer to the tables in our earnings release on the Investor Relations portion of our website for a reconciliation of these measures to the most directly comparable GAAP financial measures. With that, I'd like to turn the call over to CJ.

Thank you, Sanjit. This is my 28th day on the job, and I have been discussing with customers and our innovation teams, including the Voyage AI team and our core database teams. I believe there is a significant opportunity for MongoDB to serve as the data platform for AI workloads because real-time operational data and the right context are essential. It's crucial to keep current with both proprietary enterprise data and the learnings from LLM models. When I consider all these elements together, MongoDB has everything required to be the foundational platform for AI workloads. In my talks with customers, I found that while it's still early in the process, various productivity applications are being piloted within organizations such as banks, healthcare providers, and manufacturers. However, I haven't observed any AI agents that are running in production and fundamentally transforming businesses or improving customer service. Many pilot projects are still in progress. In contrast, I see AI-native companies experiencing rapid growth; one has recently switched from Postgres to MongoDB due to scaling issues with Postgres. Another AI company mentioned using our embeddings and vector database alongside our operational platform. Overall, I believe that MongoDB has a crucial role in enabling enterprises to develop scaled agentic platforms that can transform their businesses. From a practical standpoint, I think our embedding model and reranking model are starting points that customers can utilize today, later transitioning to our vector database for real-time operational storage. This thinking has been affirmed through initial conversations with customers.

Understood. I know it's early, so great to get that perspective. And then one follow-up for me, sort of a mark-to-market question.

Sanjit, it's Mike. So what we'll say there is, as we said during the prepared remarks, and we saw this in Q2 as well, what we're really seeing is strength in the larger customers. It's not only from new workloads, but it's from the existing workloads. We don't want to bifurcate between which calendar year those were added. What we'd say is that we continue to see growth in the larger customers. They are growing longer, and they're getting bigger and growing for longer, which is great. And we're seeing that across both the United States and then broad-based in EMEA as well. And as Atlas gets bigger and bigger, all of those kind of munch together because they're expanding and adding. So what we'll do is we'll focus on the growth in our larger customers, especially in the U.S. and EMEA without going into each year. I hope that helped.

Nice to see another quarter of acceleration. CJ, I appreciate you're only a few weeks in, but I'd be curious to hear what customers are telling you is top of mind for MongoDB. What are the repeated themes in customer conversations as you take a fresh lens to the business?

Absolutely, Matt. First thing I would say is that the modernization effort, whether it's a workload that may be just running on-prem, in a large enterprise or a workload that is moving to cloud or sometimes to multiple clouds for resiliency that transformation in speaking to a large telecommunications company, a large health care company, a large tech company, and I can cite you many other examples. I was pretty overwhelmed to understand that those transformations are still going on. There is just a recent conversation I had with the CTO of a large telecommunications company who said that they are moving 1,300-plus applications to another hyperscaler and trying to determine which workloads are best suited for MongoDB. So the whole multi-cloud or a public cloud transformation is still going on. And just my intuitive sense in speaking to these customers will be going on for at least the next 5 to 7 years. So that specific TAM still very much exists for MongoDB. Now these are the same set of customers, while they are trying to modernize their application stack, they are also experimenting, I would say, because I've not seen agents at scale that are customer-facing or sometimes even employee-facing, they may have 10, 15, 20, but not that many compared to thousands of applications they run. In those AI applications area, they are experimenting sometimes with our embedding models or with our vector database or using MongoDB for real-time operational database. So that second aspect, which is still fairly early, but we are very well positioned as you think about AI workloads in enterprises and large enterprises. And last but not least, spending time, as you know or you may know that I spent half of my time in New York City and half of my time in Silicon Valley and speaking to my network in Silicon Valley with AI-native companies or digital-native companies, what I hear from them is that certain alternatives on relational database just do not scale because AI workloads are fundamentally around unstructured and semi-structured data. And then they decide sometimes explicitly to use MongoDB. So I put this in 3 buckets. One bucket is our core and still the cloud transformation, digital transformation, modernization, whichever term you want to use, our core will still continue to grow. As people create AI agents at scale, MongoDB has a role to play and for AI-native companies and some at scale are already using MongoDB because the alternatives in the relational world just do not scale. So those are my like 3 buckets and initial mental model on how these conversations are proceeding and what we can do for them.

Really clear. And then, Mike, just a quick follow-up for you. It was good to see the outperformance on both Atlas and non-Atlas, but with op margins now about 200 basis points shy of your midterm framework, how should we think about the philosophy around reinvestment? And any considerations around non-Atlas and the ability to expand margins as we look out into fiscal '27?

Thank you for the question, Matt. I know everyone's focused on 2027. We'll provide guidance for 2027 on the next call. As mentioned in the Q4 guidance and in my prepared remarks, we are continuing to invest and will keep investing. Some investments, particularly in engineering and sales capacity, have been pushed into Q4. Therefore, you should expect operating expenses to continue to grow in fiscal 2027. We also want to emphasize that we still anticipate margin expansion, especially evident in the fiscal 2026 numbers, primarily driven by revenue growth. Our expectation for next year is to continue growing revenue and investing in the business, as our business model will support that expansion. You can expect us to keep investing, particularly in the three key areas discussed.

Okay. Great. Thank you. First of all, CJ, welcome aboard. I'm excited to work with you over the coming years. I had a question for you. So it seems as if you're describing these good set of numbers as strength in the core, essentially even before that AI tailwind kicks in. I'd love if you could define what you think is fundamentally driving that core strength? And do you feel like it's possible that actually Mongo is already getting an AI tailwind in the sense that there's a heightened focus on modernizing your data in advance of AI, such that this core strength is actually AI-related?

Karl, great to hear from you and looking forward to seeing you on Wednesday. I would say the core strength from my perspective is workloads that need modernization have a lot of unstructured or semi-structured data and ideally suited for MongoDB. Now when it comes to AI, could AI potentially drive more modernization efforts? That is possible but not deterministic. As we shared in the remarks, that in the high end of the enterprise, the consumption of the workloads we acquired maybe a year ago, 1.5 years ago, that continues to move up in the right direction as our go-to-market teams are focused on the high end of the enterprise. We also saw broad-based strength in Europe. And that is pretty much to the core business, like the large insurance company on the claims engine and other things that I spoke about related to policies. So I particularly see that as, okay, does that mean that if core is modern, it helps with AI workloads? Absolutely, that is true because they are not mutually exclusive. And one thing I would say, this is my personal experience in building AI technologies in the past. The AI team is typically a separate team from the core data team. And the AI team relies on the core data team. And if the core data team moves slow, then AI teams get really frustrated because innovation velocity is how they measure themselves on. So my personal experience was, hey, when the core team is not agile, their schemas are not flexible, it actually slows AI down. So that is definitely some facts behind your theory that it is potentially the AI revolution, which we are still in the early stages, is driving modernization in the other part of the enterprise.

So, thanks, Karl. Thank you for the question. I would say it's probably a little bit of both. One is, hey, we want to give you folks a little bit more visibility to what's behind the guidance that we provide. That was number one. Also, as Atlas gets to be, gosh, now almost a $2 billion business, we feel better about the forecasting. The team has done a wonderful job forecasting that part as well. So when we gave the number for Q4, we want to make sure and give you the visibility. But we also have a pretty good view of what we hope it would be, understanding that, keep in mind, Q4, we want to be prudent because there are some seasonal holiday patterns that can be somewhat unpredictable, and we've seen that play out in the past Q4s. So I just want to note that for the guidance that we just gave.

CJ, I wish you all the best as well. I have two questions, one for you and one for Mike. CJ, one of the key factors for Mongo's adoption will be developer engagement, as developers significantly influence usage trends. Currently, much of the AI activity is concentrated on the West Coast. How do you plan to enhance developer engagement with Mongo to counter the prevalent Postgres narrative in that area? And Mike, regarding next year, since EA will not benefit from the entire year, should we base our expectations on the ARR performance? Is that the appropriate way to approach it?

Thank you, Raimo. It's great to hear from you. I want to start with some historical context regarding your point about the West Coast. I'll ask our former CEO, Dev Ittycheria, to discuss the Reclaim the Bay initiative that he and the team initiated, and then I will share my thoughts on the situation in the West Coast.

Raimo, it's Dev here. As CJ mentioned, we've talked about this in previous calls, but we made a concerted effort to reinvest in the Bay Area because during COVID and post-COVID, we felt that we had neglected that region. And obviously, there was a whole new corpus of AI-native companies that were getting launched. So there's been a real concerted effort both in terms of putting more feet on the street, putting more marketing efforts in terms of supporting that part of the world. Investing more in the start-up community and also in the venture community to get people to understand the true value proposition of MongoDB. We've done things like hackathons and other events in that area as well. And so the team's really focused, dedicated to really supporting and servicing these early AI native companies, and that is starting to yield some results. And we feel really good about the progress there, but I'll let CJ talk about what happens going forward.

Thank you, Dev. And this is the reclaim the Bay in San Francisco on the West Coast. It is 100% true Raimo, that there is a lot of investment with AI-native companies, and we could benefit from increased mind share and being in front of them as in the developer community that you talked about, which is a super important community to us on the West Coast. So me spending personal time on the West Coast house. I do also have deep networks in the West Coast community, both venture community as well as tech companies at scale. And I've already started leveraging that network to get their feedback. We are really excited in this quarter, as in the 4Q, we are relaunching our .local after a few years in San Francisco on January 15, where we are going to invite companies that have built on MongoDB, some great speakers on why they should build on MongoDB and show hands-on experience to the developer community in that conference on January 15. And what I see is just speaking to many CEO founders as well as developers of smaller companies or midsized companies, all these efforts of the marketing investment that Mike and Dev originally approved is going to start yielding results as we move into the next fiscal year.

Thank you for your question, Raimo. It’s Mike. Regarding non-Atlas, we have received numerous inquiries about the multiyear headwind. Currently, we are not providing guidance for fiscal '27. However, as of today, I would suggest that for the full year revenue growth of non-Atlas, it is around 4%. A range of low to mid-single digits is a good estimate for next year.

Great. I'm not sure who this is for, but on the commentary around new customer strength within Atlas, are you seeing new customers ramp faster for net new workloads than they have been historically? And if so, why?

Brad, my initial observation is that the engineering team has done a fantastic job when they launch 8.0 and all the subsequent point releases that allow Atlas to be adopted faster and remove the friction, whether you are coming via our self-serve channel or whether you are a large enterprise moving onto Atlas. So that's one thing I would say. And I'm going to ask Dev to provide commentary as well from a context perspective.

Yes. I think we've really removed the friction to enable customers to onboard more quickly and easily. Given the performance gains we've seen in version 8 and even better in version 8.2, I believe that's driving much of the traction we are experiencing with our new customers. They quickly recognize the performance benefits and are scaling effectively. This is allowing us to continue acquiring customers efficiently.

And one last thing on that, Brad. If you look at the revenue from that, it hasn't changed materially. It's still, keep in mind, a pretty small number when they first onboard, so it's not going to move the needle much. We haven't seen much change in that cohort over the last couple of years.

Great. And then, CJ, a quick follow-up for you. Philosophically, how do you think about M&A as it relates to Mongo? What types of things, if anything, do you think you need to acquire?

Brad, you know me well, and I'm a big believer in organic growth. The team, Dev and the team have laid a very strong foundation on our technology platform. I think Voyage AI in February was a brilliant acquisition, where we got an unbelievable team in Palo Alto. And my goal on behalf of MongoDB is to always believe in our own teams and our technology. We participate in a large market and where it makes sense, where we can get a particular adjacent technology or a great team that can help us accelerate the roadmap, we would always consider that type of M&A.

CJ, maybe for you. I mean, you shared, I think, a lot of thoughts about your initial vision. You shared the 3 pillars of the core, the enterprise AI opportunity, and the AI natives. I just want to maybe lean in, where do you see your particular skill set of network offering kind of not the lowest hanging fruit, but your ability to make kind of the biggest impact in, call it, the next 12 to 24 months? Like where do you really see that incremental opportunity for growth inflection?

I believe that there are two main areas where I can significantly benefit our go-to-market teams. First is the Fortune 500 sector, where MongoDB has the potential to grow at an even faster rate, both with existing clients and new ones. I also spent time with our sales teams in Europe, where they are focusing on existing clients like large banks and manufacturing companies, and my relationships with technology decision-makers can really assist in this area. The second area is with AI-native companies. Having lived in Silicon Valley for a long time, I have a good understanding of where the venture community is investing, particularly in domain-specific and foundational AI companies. I plan to cultivate these relationships so that in due time, they can become a significant business for MongoDB if we become their underlying infrastructure. So, those are the two areas where I will be dedicating a lot of my time.

Excellent. You mentioned that the acquisition of Voyage AI this year is a significant addition to the portfolio. Can you help us understand the opportunities with the AI native aspect? Are you seeing success with Voyage? Are you making progress with Atlas? Are you seeing consistent results from both now? Please clarify what sets these apart incrementally.

Yes. I would say one example, and this in my remarks, I shared that there is a super high growth AI company that is doing very, very well and will become a very large company. I have absolutely no doubts about that. They were not able to scale with Postgres and few other technologies, Redis, and so on that they were using, and they moved completely to MongoDB and seeing that week-over-week and month-over-month growth is super inspiring. And I spoke to the hyperscaler where this workload is running, and they are seeing the same that, wow, this company is doing really well. So that's built on MongoDB because Postgres had scaling issues. The other extreme, I spoke to a fairly successful AI native company that is doing decent ARR, growing very fast. And when I said, hey, have you considered MongoDB to the founder, CEO, who is very technical? And he said, CJ, we didn't. We built our own vector database and so on, and while I was speaking to him Alex, about 10 days ago, he basically said, once he looked at the portfolio, he said, let me start with embeddings first. So we are going to try. Of course, we have to prove to him why our embeddings improve his accuracy on search and so on and improve the performance. So he said, let's start with embedding models first from Voyage AI once that works, CJ, I'm willing to replace my vector DB that we have homegrown created it with MongoDB, and oh, by the way, if that works well, eventually, I'm willing to swap out my operational database as well and use MongoDB. So in those kinds of scenarios where they are already on a certain track, we can land with Voyage AI embeddings. And I'm also seeing in a very large customer of MongoDB, I spoke to somebody who is running the AI initiatives, and they love the Voyage AI embeddings and reranking model, and they've already approved it for 2 big workloads. So we can absolutely land with that is the short answer.

The consumer app development environment is getting stronger as new iOS app development has surged multiyear highs. We think it's due to agentic coding, And I know it's early but on the enterprise side, are you seeing stronger product velocity from your customers in building their enterprise applications?

I'm going to ask Dev to provide his opinion, and then I'll provide mine.

Yes, what we're observing is a significant amount of prototyping and iteration. The enterprise requirements remain quite demanding in terms of security, durability, and performance. There is a considerable distinction between launching a prototype and having a fully reliable, production-grade system that enterprises can trust. Therefore, considerable effort is still needed to elevate those applications to enterprise standards. However, with the emergence of cogen tools, the speed and volume of software development are set to accelerate. As we've mentioned before, this is one of the main reasons we see AI as a beneficial factor. The capacity to create more encapsulated software is growing, which is positive news for us.

Yes. I want to add that when I talk to customers I've been engaged with for a long time, particularly in regulated sectors like financial services, healthcare, and the public sector, the needs for AI agents in production versus prototypes are significantly different. These customers are seeking governance and auditability, while also emphasizing the importance of innovation and speed. However, when I inquire about their agents in production, they often reveal that many are not truly customer-facing or fully auditable in terms of their probabilistic outcomes. They mention they are still working through these challenges. This doesn't mean progress won't happen soon, but I believe we are still at an early stage. Additionally, they are experimenting with various agents, and the churn among AI companies providing these solutions is notably significant. This is why I’m optimistic about the opportunity with MongoDB. We have a solid platform for operational data, the best vector database, and embedding models that enable enterprise-scale development of genuine AI agents using our platform.

Yes, thanks. I won't use a golf analogy, and I prefer hockey analogies. I want to say that we feel really positive about Atlas. It has performed well this year, and we are optimistic about its prospects heading into Q4. We remain excited about its growth. However, we are being cautious for Q4 due to the seasonal holiday trends, which can be somewhat unpredictable, as we've experienced in previous Q4s. So, we just need to be careful as we approach the holiday season.

Thank you, Lisa. In summary, we delivered an exceptional third quarter, highlighted by accelerating Atlas growth, robust customer additions, and significant operating margin outperformance. We are raising our revenue and operating income guidance for the fourth quarter and full fiscal year 2026 and reiterating our commitment to the long-term financial model we outlined at Investor Day. Our results underscore that MongoDB's core business is firing on all cylinders even before any meaningful AI tailwinds. At the same time, we are uniquely positioned to become the generational modern data platform for the AI era, all while driving durable, efficient growth. Thank you, everyone, for joining, and thank you for listening.

This does conclude today's conference call. You may all disconnect.