Title

Presentation

Elastic N.V. beats earnings expectations. Reported EPS is $0.63, expectations were $0.47.

Operator: Good day, and welcome to the Elastic Third Quarter Fiscal 2025 Earnings Results Call. All participants will be in a listen-only mode. [Operator Instructions] After today’s presentation, there will be an opportunity to ask questions. [Operator Instructions] Please note this event is being recorded. I would now like to turn the conference over to Mr. Anthony Luscri, Vice President, Investor Relations. Please go ahead, sir.

Anthony Luscri: Thank you. Good afternoon, and thank you for joining us on today’s conference call to discuss Elastic’s third quarter Fiscal 2025 Financial Results. On the call, we have Ashutosh Kulkarni, Chief Executive Officer; and Eric Prengel, Interim CFO and GVP of Finance. Following their prepared remarks, we will take questions. Our press release was issued today after the closed market and is posted on our website. Slides, which are supplemental to the call can also be found on the Elastic Investor Relations website at ir.elastic.co. Our discussion will include forward-looking statements, which may include predictions, estimates, or expectations regarding the demand of our products and solutions and our future revenue and other information.

These forward-looking statements are based on factors currently known to us, speak only as of the date of this call and are subject to risks and uncertainties that could cause actual results to differ materially. We disclaim any obligation to update or revise these forward-looking statements unless required by law. Please refer to the risks and uncertainties included in the press release that we issued earlier today, included in the slides posted on the Investor Relations website and those more fully described in our filings with the Securities and Exchange Commission. We will also discuss certain non-GAAP financial measures. Disclosures regarding non-GAAP measures, including reconciliations with the most comparable GAAP measures can be found in the press release and slides.

The webcast replay of this call will be available on our company website under the Investor Relations link. Our fourth quarter fiscal 2025 quiet period begins at the close of business on Wednesday, April 16, 2025. We will be participating in the Morgan Stanley Technology Media and Telecom Conference on March 5 and the Wells Fargo Software Symposium on April 10. With that, I’ll turn it over to Ash.

Ashutosh Kulkarni: Thank you, Anthony, and thank you all for joining us today. Our Q3 results reflect ongoing momentum across all aspects of our business, led by our strong sales execution, continued market demand for our products and our relentless space of innovation. With strong contributions across all solution areas, search, observability, and security, we delivered an outstanding quarter, outperforming our guidance metrics. Total revenue grew 17% year-over-year with cloud revenue growing 26% year-over-year and our non-GAAP operating margin represented 17% of revenue. The number of customers spending over $100,000 with us increased to over 1,460 during the quarter, demonstrating the strength of our land and expand motion.

Consolidation and generative AI are powerful tailwinds, driving momentum at Elastic and at the forefront of our interactions with customers and prospects, especially as customers continue to prioritize innovation and efficiency across their businesses. During the quarter, we saw continued progress in our go-to-market motion. At the start of this fiscal year, we implemented field segmentation changes that increased our focus on landing and expanding enterprise and high-potential mid-market customers. These changes resulted in some unanticipated sales execution issues in Q1 that we have since been addressing. Our performance in Q3 demonstrates that we are now back to the levels of sales execution that we have seen in the past and we are even starting to see the expected positive impact from the earlier segmentation changes.

Q3 performance benefited from our maniacal focus on these customer segments and deal flow remained strong during the quarter as we grew commitments from new and existing customers across all of our solutions. To that point, we have already added significantly more customers spending over $1 million with us through the first three quarters of this fiscal year versus all of last year. Generative AI is enabling organizations to extract value from unstructured data, documents and logs. Search is core to value extraction, and we saw outperformance from search in Q3 with our search business once again accelerating year-over-year. We are seeing an evolution of search with customers moving from textual search to semantic search and then building conversational applications using retrieval-augmented generation or RAG.

As enterprises experiment with and adopt agentic workflows to automate multi-step business processes, the importance of search for powering AI will continue to grow. Customers are choosing the Elastic search AI platform as an essential layer on which to build all of these flavors of new search-powered applications and we expect this momentum will continue to form a tailwind for our business for many years to come. Our vector database resonates with customers. In addition to our best-in-class vector database, we are taking a distinct approach, offering customers an efficient way to create, store and search vector embeddings beyond those provided by point solution vector databases. In Q3, we signed a seven-figure deal with the digital-native career platform, displacing a competitor’s vector database as the company scales their business globally and creates new Gen AI-based customer experiences.

The Elastic Search AI platform provides a complete search experience within a single platform, allowing the customer to evolve and deploy critical functionality without the complications of managing third-party APIs. We are seeing a positive impact from our leadership position in Gen AI on our business. In the quarter, we signed five deals of greater than $1 million in annual contract value where customers are building Gen AI applications using Elastic, building upon our momentum in Q2. Now over 1,750 Elastic Cloud customers are using us for Gen AI use cases with over 270 of these customers spending $100,000 or more with us annually. We believe that as more companies leverage large language models to create new customer experiences, automate business processes involving unstructured information and evolve work streams toward agentic AI use cases, we will benefit.

Elastic has the power to bring all these pieces together to be the runtime platform for Gen AI applications that simplifies developer experiences and drives greater efficiency and accuracy. Outside of Gen AI, we also see strength with our observability and security solutions as customers continue to consolidate onto our platform. In observability, our strategy centers on logs, knowing that they are a rich data source for monitoring mission-critical systems and often represent the messiest data that is challenging to analyze. Elastic excels at transforming logs into understandable, searchable and analyzable formats, a key reason for why we win with customers. Our unified data store with our emphasis on extremely efficient storage makes it possible for customers to correlate log data with metrics, APM traces, and other observability signals at a massive scale, making our solution incredibly compelling for enterprises.

Our investments in pattern analysis, machine learning, and GenAI reflect an evolution from traditional monitoring to a modern approach that reveals the unknowns in complex systems. New product releases like logsdb index mode continued to differentiate our solution from competitors. In another competitive win from the quarter, we signed a seven-figure deal with an industry leader in smart water management. The customer expanded its use of Elastic Search and Elastic Observability to enhance operational efficiency and customer service. We power their analytics and billing platform, which ingests millions of water meter readings daily, enabling them to proactively identify anomalies and resolve issues to ensure their systems run effectively. Logsdb index mode was a key factor in how we’ve outperformed two competitors with features that optimize data, ordering, and storage and reduced query latency, showcasing our scalability and ability to deliver accurate results.

Additionally, they have now started to build RAG powered conversational app on our Search AI platform to strengthen customer service. In security, AI-driven security and information management or SIM transforms the modern SOC by automating and simplifying processes, helping practitioners work more efficiently and effectively than traditional SIM solutions. In 2024, we released our attack discovery solution, leveraging large language models to automate threat discovery. I’m pleased to report that we are seeing strong interest from customers looking to enhance their SOC operations and we have received positive feedback from industry analysts around this ground-breaking functionality. In a new seven-figure deal, a military unit responsible for overseeing software capabilities and development for U.S. government use shows Elastic Security SIM and endpoint capabilities to support military operation centers.

Elastic was selected over competitors for a compelling total cost of ownership. These SOC environments ingest terabytes worth of logs per day and Elastic’s cross-cluster search and replication capabilities facilitate efficient workflows for the customer. The customer intends to implement attack discovery to streamline alerts once their Elastic Security deployments are fully operational. Customer consolidation onto our platform drove multiple wins during the quarter as we continue to benefit from the secular tailwind. By helping customers reduce complexity and drive efficiency at a lower total cost of ownership, we are securing solid commitments and becoming an increasingly strategic part of their IT infrastructure. Madrid Digital, a government agency responsible for the digital transformation of one of Europe’s largest capital cities, signed a new agreement with Elastic in a seven-figure multi-year deal for Elastic Observability.

The customer moved from an open-source version to Elastic Cloud to consolidate multiple tools onto a single platform and modernize its infrastructure. Madrid Digital provides diverse services for its 7 million constituents, requiring a solution to effectively monitor over three terabytes of logs per day and reduce the average resolution times for technical incidents. They chose Elastic Observability over competitors due to our scalability and product features like cross-cluster search and our AI assistant. Now turning to product innovations during the third quarter. We released Elastic Cloud Serverless, which is now in general availability on AWS and technical preview on Azure with general availability expected in March. Though in the early stages of our journey, we are starting to see momentum with customers.

Elastic Cloud Serverless is the fastest way to access Elastic Search, Elastic Observability, and Elastic Security. We offer customers a dedicated offering for each solution with distinct pricing and experiences to match different underlying personas. One Elastic Serverless customer, SAP Concur, highlighted that it takes virtually no time to set up a new project, emphasizing its autoscaling capabilities. Our industry-first Search AI Lake serves as the foundation of our serverless architecture, allowing for low latency querying across all data with the precision of search. As a fully managed offering, Elastic Cloud Serverless reduces the configuration burden for our customers so that they can run faster to their desired end state. We will launch support for Google Cloud instances as we continue to expand this offering to all three major hyperscalers in the coming months.

The general availability of Elastic Search logsdb Index Mode, which is available in our enterprise tier was another milestone release during the quarter. LogsDB Index Mode makes Elastic Search more efficient and encourages customers to do more with Elastic. By optimizing data storage, indexing, and management, we help our customers extract more value from logs while reducing the total cost of ownership. Similar to our release of searchable snapshots in 2020, the cost savings of logsdb Index Mode pushes customers towards the enterprise tier, incentivizing customers to move over workloads from competitive products and consolidate more onto our platform. Data consolidation onto Elastic’s Search AI platform unlocks more value from the underlying data as customers leverage search AI across our solutions.

Customers are expanding their use of Elasticsearch due to logsdb Index Mode. During the quarter, a global software company and longtime Elastic Search customer upgraded to Elastic Cloud Enterprise from the Platinum tier to access all capabilities of logsdb Index mode in a seven-figure deal. The customer’s previous logging estate was fragmented with multiple tools and inconsistent standards, hindering efficient analysis and troubleshooting. Elasticsearch will be providing better logging infrastructure at a compelling total cost of ownership, allowing them to consolidate tools and modernize the observability stack. The customer also chose Elasticsearch as their end-to-end rack solution to jumpstart their AI journey and accelerate their ability to ship GenAI features rapidly to their customers.

Our Rerank model differentiated our platform from competitors, improving accuracy and reducing latency while remaining affordable. We released the Elastic Rerank model in tech preview during the quarter. Our Rerank model boosts search results with more relevance. For RAC, providing precise context from the user’s data to large language models helps ensure accuracy of responses and reduces costs by improving the semantic relevance of each query. Similar to the blueprint of our ELSER model, we designed Rerank to be high-performing with relatively low resource requirements. While our architecture supports integration with third-party models, we are also building our own embedding and Reranking models, up-leveling our platform to a holistic solution where customers can adopt certified components from Elastic into their infrastructure.

Q3 brought several major opportunities to connect with and learn from our customers, developers, IT professionals, and partners. We continued our ElasticON conference in Amsterdam, Paris, and London, where our team and I were on the ground engaging with thousands of customers and prospects interested in learning more about how to get the most from Elasticsearch AI platform. In November, we attended AWS Reinvent, where we were honored with the AWS Global Generative AI Infrastructure and Data Partner of the Year award, a testament to our strong partnership with AWS and recognition of our work to help customers develop and scale their GenAI capabilities. Today, we are also announcing that Navam Welihinda will be joining Elastic as our CFO starting February 28.

Navam was most recently the CFO of Grammarly and prior to that spent seven years at HashiCorp, where he helped lead them through many milestones, including their IPO and successful growth to over $650 million in revenue run rate. Prior to HashiCorp, Navam spent time in finance leadership roles at IBM and Deem, before which he spent time in venture capital at Sierra Ventures and Inside Venture Partners. I’m very excited to have Navam join our senior leadership team, especially given his experience with opensource and consumption-based businesses. We have an incredible finance team here at Elastic and I’m confident that together with Navam, they will help guide Elastic forward to newer and greater business milestones towards becoming a generational company.

I would also like to thank Eric Prengel, who has done a tremendous job as Interim CFO these past several months and who continues to be a trusted senior leader within the company. Eric will now report to Navam and continue leading finance strategy and FP&A in addition to some new responsibilities. I’m looking forward to working very closely with both him and Navam in the years ahead. In closing, I am energized by the momentum building in our business and our strong performance this quarter. Thank you to all of our employees for their dedicated execution and to our customers, partners, and investors for their ongoing support and confidence. I’ll turn it over to Eric to review our financial results in more detail.

Eric Prengel: Thank you, Ash, for your kind words and the trust you placed in me as Interim CFO. I had the opportunity to work with Navam while he was at HashiCorp and I was at JPMorgan and I think very highly of him and all that he will bring to Elastic. Now, let’s get into the numbers. We were pleased that we outperformed against the high end of both our revenue and profitability guidance ranges, driven by another quarter of strong execution, bolstered by strong customer commitments and ongoing tailwinds from our solutions for Gen AI. Total revenue in the third quarter was $382 million, up 17% year-over-year on both an as-reported and constant-currency basis. Subscription revenue in the third quarter totaled $358 million, up 16% year-over-year on an as-reported basis and 17% in constant currency.

Within subscriptions, revenue from Elastic Cloud was $180 million, growing 26% year-over-year on both an as-reported and constant currency basis. Elastic Cloud represented 47% of total revenue and for the first time ever crossed 50% of total subscription revenue in the quarter. Aggregate consumption trends in the third quarter remained healthy with stronger-than-expected consumption revenue coming from some of our larger customers. Revenue from our Elastic Cloud month-to-month motion, which is driven mainly by self-service SMB customers was consistent with our expectations and remained flattish in dollar terms, coming in at 13% of total revenue. Professional services revenue was $24 million, growing 18% year-over-year on both an as-reported and constant-currency basis.

As a reminder, professional services revenue may fluctuate across quarters depending on the timing of service delivery. We saw strong field execution and healthy growth across our solutions where Search saw ongoing momentum from Gen AI and continued to be the fastest growing of our three solutions. The quarter’s strength is also balanced across geographies, where the Americas grew the fastest, followed by EMEA and APJ. We saw customers make strong multiyear commitments this quarter, reflecting their long-term commitments to standardize on Elastic as their platform of choice. Turning to customer metrics, we ended the third quarter with over 1,460 customers with annual contract values more than $100,000. We continue to focus on customers with a higher propensity for growth and target these types of customers in the enterprise and commercial segments, providing a strong foundation for our land and expand motion as we continue to scale.

Looking at customer additions more broadly, we ended the quarter with 4,540 customers above $10,000 in ACV and approximately 21,350 total subscription customers. Our net expansion rate was approximately 112%, consistent with last quarter and in line with our expectations. Now turning to profitability and cash flow, for which I’ll discuss non-GAAP measures. Gross margin in the quarter was 76.7%, consistent with the past several quarters. Our operating margin in the quarter was 16.8%, which was better than expected, driven primarily by our strong revenue outperformance as well as our continued discipline in spending. Diluted earnings per share in the third quarter was $0.63. Adjusted free cash flow was approximately $99 million in the third quarter, which translated to a 26% adjusted free cash flow margin.

Cash flow can fluctuate on a quarterly basis given timing issues and seasonality. So we continue to look at this primarily on a full-year basis. Although we don’t formally guide to cash flow, given the performance in the business through the first three quarters, we now expect adjusted free cash flow margin for fiscal ’25 to be a few points above the non-GAAP operating margin for fiscal ’25. As you know, our adjusted free cash flow is on an unlevered basis. Now turning to guidance. We were pleased with the continued improvements in our sales execution in the third quarter. Our guidance philosophy remains unchanged, and we continue to be prudent in the near term. We are actively monitoring the many moving parts in the markets in which we operate, including the U.S. public sector.

We remain focused on execution and believe that with our highly differentiated platform and the cost of functionality value we offer to our customers, we are well-positioned for long-term growth and profitability. Given the revenue outperformance and continued strong go-to-market execution in the third quarter, we are raising our full-year total revenue outlook. I’ll highlight some of the factors we considered in our guidance. While our performance in Q2 and Q3 gives us increased confidence in our sales execution, the shortfall in customer commitments that we experienced in the first quarter of this year will remain a headwind to year-over-year revenue growth in the fourth quarter. Also, keep in mind, in Q4, we have three fewer days than we had in each of the first three quarters of the year, which will create a sequential headwind of roughly $10 million to revenue in Q4.

We are estimating a revenue headwind versus Q3 related to the recent strength in the US dollar of about $1 million to $2 million. We continue to expect revenue from our month-to-month motion on Elastic Cloud will remain flat. Given the consumption revenue on both annual and month-to-month terms can fluctuate and taking into account all the factors I just mentioned, we have been prudent in our assumptions on cloud revenue in Q4. With the strong operating margin we have seen so far this year and the leverage inherent in our business model, we are also raising our profitability guidance for the full year. Given the opportunity in front of us and the improvements we have been seeing in our sales execution, we will continue to invest in our business in Q4, while balancing revenue growth and profitability for the long term.

Additionally, as is typical with prior Q4 periods, we expect to see seasonally higher expenses related to the timing of employee benefit costs. These expenses were already part of the guidance that we initially laid out for the year. So with all that as a backdrop, for the fourth quarter of fiscal ’25, we expect total revenue in the range of $379 million to $381 million. This represents 13% year-over-year growth at the midpoint on an as-reported basis and 15% year-over-year growth at the midpoint in constant-currency. We expect non-GAAP operating margin for the fourth quarter of fiscal ’25 to be approximately 13.5% and non-GAAP diluted earnings per share in the range of $0.36 to $0.37 using between 107.5 million and 108.5 million diluted weighted average ordinary shares outstanding.

For full fiscal ’25, we expect total revenue in the range of $1.474 billion to $1.476 billion. This represents 16% year-over-year growth at the midpoint and 17% year-over-year growth at the midpoint in constant currency. We expect non-GAAP operating margin for full-fiscal ’25 to be approximately 14.7% and non-GAAP diluted earnings per share in the range of $1.91 to $1.96 using between 106 million and 108 million diluted weighted average ordinary shares outstanding. Finally, looking ahead to fiscal ’26, our market opportunity remains large. The Elastic Search AI platform is highly differentiated, our Gen AI traction is strong, and customers are continuing to consolidate workloads onto our platform. As we go through our planning process, we expect to continue to balance investing for revenue growth with profitability.

We will prioritize investments towards areas intended to drive growth, particularly in Gen AI. We will provide guidance for FY ’26 on the Q4 call, but in the meantime, let me share our preliminary thoughts on how we are approaching next year from an investment perspective. Over the past several years, we have demonstrated that our business model has inherent operating leverage as we have expanded non-GAAP operating margin while maintaining strong top line growth. Given the Gen AI opportunity ahead of us, we intend to continue to make investments across the business to drive revenue growth over the longer term. As such, we expect to expand non-GAAP operating margin only modestly in fiscal ’26 relative to our current non-GAAP operating margin guidance for fiscal ’25.

We expect these investments to be more front-end loaded in fiscal ’26 as our sales kick off and engineering Global All Hands will both be in Q1 of FY ’26. We will provide more detail on our Q4 earnings call. In summary, we are pleased with our performance in the third quarter and remain confident in our ability to continue to drive profitable growth going forward. And with that, let’s go ahead and take questions. Operator?

Operator: Thank you. We will now begin the question-and-answer session. [Operator Instructions] And the first question will come from Pinjalim Bora with JPMorgan. Please go ahead.

Pinjalim Bora: Oh, great. Thank you so much for taking the question and congrats on a spectacular quarter here. I wanted to understand the cloud strength a bit. Because when we were going into the second half, I guess you were talking about the potential moderation given the Q1 execution issues, but seems like the sequential growth was higher than even the quarter a year ago . So it’s almost like Elastic found a new gear somewhere. So trying to understand what surprised you positively, specifically on the cloud strength and how should we think of the sustainability of that strength?

Ashutosh Kulkarni: Yes. Thanks, Pinjalim. We were happy with the Q3 outperformance, which was driven by both strong customer commitments and healthy consumption levels in the cloud. In terms of the cloud, we saw healthy consumption from both enterprise and commercial accounts in Q3 and then there was strength from some larger customers. We’ve seen the — obviously, in addition to that, we’ve seen, as we think about month-to-month, we’ve seen that to be flattish and we don’t think that that’s necessarily going to change going forward. But that strength from the enterprise and from the commercial was really powerful in Q3 and was great. As we think about looking forward to Q4, we don’t think that, we’ve tried to be appropriately prudent and we don’t anticipate that we want to bake into our guide that we’re going to see that same sequential strength that we saw between Q2 and Q3. And so the Q4 guide is appropriately prudent based on that.

Pinjalim Bora: Yes, understood. Thanks, Eric. And one for Ash. Ash, the serverless product, I want to understand something from a long-term perspective. What is the vision around that, I mean, I’m trying to think serverless obviously dramatically improves kind of the ease of use, aligns resources, cost to usage more linearly. So is the long-term vision to essentially have serverless as the core product with kind of a set of migration plan for existing customers over multiple years, or will it just exist as a choice across your self-managed as well as cloud. And help us understand kind of the impact on the P&L, how should we see it as serverless becomes a bigger part of the mix.

Ashutosh Kulkarni: Yes. Thanks for the question, Pinjalim. So as you think about serverless, there are a few things about it that we are really excited about. First and foremost, like you said, it’s a much better user experience, much faster for users to get started. And there is almost no management effort involved, right. You don’t have to worry about setting up the cluster, managing it, scaling it, everything is done automatically for you. The second thing is the pricing model like you talked about. The third thing is for Elastic, we are able to manage that environment much more efficiently because of how it’s architected, because of the search AI lake architecture that underpins serverless. So our long-term vision is, if I look ahead a few years, serverless is going to be the primary way in which our customers experience Elastic cloud.

And over time, we’re going to provide migration tools. There’s more functionality that we are adding to Serverless right now. We need to have it available in all the three hyperscalers. We want to build it out in multiple regions across these hyperscalers. But as we do that and we deliver migration tools, our expectation is that more and more of the workloads will move there and eventually that will be the thing. And like we’ve talked about in the past, there are lots of values even to our business in terms of how we can better capture some of the gross margin benefit from it. So now to talk about how to think about the financial model, Eric.

Eric Prengel: Thanks, Ash, and I’ll just add a few things. Obviously, it’s going to take time to feel the financial impact as we’re still in the early days. We just went into GA with AWS and Azure is in a tech preview. We’re going to be live on all three of the hyperscalers in the near term. We think that serverless can be a growth driver for the cloud business as it’s going to make it easier to get up and running on Elastic. And then one last thing, Ash touched on this a little bit, but we do think that it’s going to be an uplift to our gross margin as it’s a more efficient way for us to utilize cloud resources.

Pinjalim Bora: Understood. Thank you very much.

Operator: The next question will come from Raimo Lenschow with Barclays. Please go ahead.

Raimo Lenschow: Hey, thank you. And congrats from me as well. The two questions I had. One is on the, if you think about the self-service part of the business, like how do we think about what you saw that this quarter, how does that kind of relate also for what we saw, how the sales changed at the beginning of the year kind of impact things there? Can you just speak to that part of the business and I have one follow-up.

Ashutosh Kulkarni: Yes. Maybe I’ll touch upon that. So if you think about the self-service cloud business, that is targeted towards largely the SMB segment, right. And our sales-led motion focuses on our enterprise and mid-market customers. And for the SMB segment, we’ve targeted through this self-service, monthly cloud motion. That monthly cloud motion, that self-service cloud motion remained pretty much consistent with what we’ve seen in recent quarters. It was flattish. And that’s far more correlated in our view with what’s happening in that segment of the market, the SMB segment as opposed to anything else. And on the sales-led motion, like I mentioned in my prepared remarks, I’m very happy with the performance that we’ve seen through our sales execution and everything in terms of building pipeline, progressing pipeline and closing deals and securing commitments, all of that is back to the kind of pace that we’ve seen in the past. So very happy about that.

Raimo Lenschow: Perfect. And then more a technical one now. On security — on the security event management space, you talked about the evolution there. What are you seeing there in terms of willingness of customers to think about kind of moving not just the logs to you, but kind of going there as well. Obviously, there is a legacy player that is now part of a bigger entity and where like then discussion becomes like, well, actually, do you need to continue to pay the higher price there? What are you seeing there on the SMB space? Thank you.

Ashutosh Kulkarni: Yes. We are seeing a lot of interest in customers that are looking for two things. One, they’re looking for more AI-led automation. You know, it’s — security is, at the end of the day, a data problem. And as attacks are becoming more and more sophisticated, it’s becoming very clear that; A, you need to be able to look across all of your data sets very fast. And second, you need to be able to go back in time and see data that you might have retained over a period of years to understand whether those patterns were ever seen before. And we can do that at massive scale, like a lot of the innovations that we’ve driven to make are the way we store information more efficiently, the way we analyze it using machine-learning, our AI functionality like Attack Discovery, all of those are big differentiators.

And then obviously, like we’ve talked about the value for cost that we are able to deliver is a tremendous advantage. So those two things taken together are helping us secure wins and a lot of customers are sort of looking at those two things with a view of consolidating onto our platform.

Raimo Lenschow: Perfect. Thank you. Congrats.

Operator: Your next question will come from Sanjit Singh with Morgan Stanley. Please go ahead.

Sanjit Singh: Yes, thank you for taking the questions and congrats on Q4. Just talking about the stronger growth in cloud. I wanted to just get a sense of how much of it has been driven by sort of consolidation opportunities, whether it’s on the security side or the observability side versus, let’s say, Gen AI. Is Gen AI and Azure starting to move the needle when we think about either year-over-year or sequential dollar growth?

Ashutosh Kulkarni: Yes. Sanjit, thanks for the question. So the strength that we’ve seen has been across the entire business, across all parts of our business, search and in search, it’s obviously a lot of Gen AI, but then also observability and security where we continue to see consolidation onto our platform. I talked in our prepared remarks about some of the customer wins where logsdb index mode has been a factor in helping customers consolidate onto our platform, bring more workloads onto our platform. And at the same time, we’ve also seen some really wonderful wins on the Gen AI side, customers choosing us as an entire runtime platform and using not just our vector database, but a lot of the other functionalities that we’ve delivered, things like our ELSER embedding model, our re-ranking model, which we recently introduced, our playground.

So we are seeing customers use us more and more as a runtime for building these RAG applications, but the strength was broad-based. Eric, anything to add to that?

Eric Prengel: Yes. I would just say the same that Ash said. I think we had healthy consumption across the board. We saw an acceleration sequentially in some of the larger customers and it was, we talked about that in Q2 and they were actually a different set of customers in Q2 and Q3. But overall, we are happy with what we saw in the consumption business.

Sanjit Singh: Understood. And then just for a follow-up on sort of the vector search opportunity. A lot of this has been focused on early RAG style use cases, chatbots, and the like. As we sort of move to agentic architectures, sort of serving as a memory for agents, is that a bigger opportunity? Is that more sort of compute-intensive in some sense than what we’ve seen thus far in terms of some of these early RAG use cases. Just wanted to get a sense of if the team has a point of view on what supporting agents from a memory perspective, what that opportunity looks like for Elastic.

Ashutosh Kulkarni: Yes, Sanjit, the way I would think about it is it’s creating more kinds of applications and more applications that require retrieval. So, it’s just increasing the total addressable domain for us. What we are seeing is that customers started that — our traditional customers have always started with us with textual search and those customers first started moving towards semantic search, then they started building conversational apps, now customers are looking at how they can automate business processes with these Agentic workflows. But effectively, what those Agentic workflows end up being is like you said, they are multistep processes that these Agentic models are orchestrating and each of those steps in those workflow effectively need some way to ground your large language models, your inference models, and that’s where we come in, that’s where our retrieval engine comes in, and that just means that there is more utilization and more usage for Elastic in the coming years and that’s what’s really exciting about what’s happening with GenAI.

Sanjit Singh: Very interesting. Congrats again on the quarter.

Operator: The next question will come from Matt Hedberg with RBC Capital Markets. Please go ahead.

Matt Hedberg: Great. Thanks for taking my questions, guys. Congrats from me on the quarter as well. Really great to see the momentum, especially after Q1. Ash, for you, GenAI continues to resonate vector, continues to resonate, I guess I’m wondering, to me, it feels like that’s now the tip of the spear. I’m kind of curious, is that the case for like a lot of new customer inbound? And then ultimately, how does that help the other aspects of your business like Observability and Security?

Ashutosh Kulkarni: Yes, it’s a great question. And absolutely, GenAI is probably one of the most leading discussions that we tend to have in the field with our customers. There is a lot of interest in — it’s because it’s — there’s a demand within the customer base for building all these kinds of different GenAI applications that we talked about. Agenetic workflows are a topic of discussion in a lot of organizations, and what that means is more opportunities for us to come and position not only what we can do with our vector database and our runtime platform for RAG, but then also talk about how we can with that same platform help our customers consolidate more of their workloads onto Elastic, reduce their overall spend by displacing incumbents that might not be innovating as well, not as focused on AI and ML and so on.

And so you have seen us come up with functionality in the area of observability and the area of security, be that our AI assistance, things like Attack Discovery on the security side, all of those are helping us compete better, take more share in these other business spaces as well. So absolutely, AI is the tip of the spear, but it’s helping all parts of our business.

Eric Prengel: The one thing I’d add to that is that, as you think about GenAI and how it impacts our business, it’s really a strong tailwind across all three of the solution areas. It makes the TAM bigger for search and we’re a leader in that space. And then in terms of security and observability, given that there’s so much GenAI really embedded in our platform, it makes us much more competitive in those spaces.

Matt Hedberg: Well, and that really — that’s kind of what I’m hearing from some of the field work that we’re doing and it just makes the entire Elastic platform more relevant. And I guess maybe just as a follow-up, I know, especially now with Elastic Cloud and more than 50% of the mix, you have a better sense for usage on the platform, do you have a rough approximation just given how really it feels like all kind of three aspects of the business are growing fast? What the rough mix is these days between Search, Observability, and Security? Thanks again for the questions, guys.

Eric Prengel: Yes, historically, we’ve shared some metrics around what that’s looked like from a commitment level, and what we’ve shared is that it’s about 40% of that business is coming from observability, about a quarter of the business comes from security, and the rest comes from search. Over the last couple of quarters, we’ve seen search grow really nicely and it has been the fastest growing part of our business and that’s really been driven by GenAI, but nothing that we call out to date that’s fundamentally a change from what we’ve said historically.

Ashutosh Kulkarni: And what I’d say is like keep in mind that like we said this quarter, like the strength was pretty broad-based and we are seeing the obvious benefits of GenAI on the search side, but it’s also helping us drive more competitively on the observability and security side. And this was the bet that we had made that AI was going to help us across the board and so we invested early and we are seeing the benefits of that.

Matt Hedberg: Thanks, guys.

Operator: The next question will come from Rob Owens with Piper Sandler. Please go ahead.

Rob Owens: Great. Thanks for taking my question. In your prepared remarks, you did talk about your progress from a go-to-market perspective around land and expand, and clearly, the larger deals are showing momentum, but was curious from a land perspective, the customer count was a little weaker than you had seen previously. So any color you could add would be helpful. Thanks.

Ashutosh Kulkarni: Yes. So let me maybe take that and then I’ll invite Eric if he wants to add anything more. From our perspective, our focus has been on our enterprise and mid-market high propensity customers. That’s really what we focus most on internally within the company. Our sales-driven motion is all tuned towards that, and that’s why as you think about our land and expand motion, the metrics that we really care about are the number of customers spending over 100K with us and we are going to continue focusing on that area. I think one of the things that I also shared was that in the first three quarters of this year, we significantly added more million-dollar customers than we did in all of last fiscal year. So you’re seeing the benefits of the work that we’ve been doing in this area, and I’m really happy about that.

Eric Prengel: I’d just reiterate what Ash said. We’re less focused on total customers and more focused on those higher-value customers with a higher propensity to spend with us, and so as we think about those 100K customers and $1 million-plus customers, that’s where our focus is. And we’re really happy with the way that our go-to-market is executed in Q3 and also as well as Q2, we’re really driving penetration into these larger customer accounts, and so we’re happy with the way it’s been working.

Rob Owens: Thanks for the color.

Operator: The next question will come from Howard Ma with Guggenheim Securities. Please go ahead.

Howard Ma: Great. Thanks so much. And I want to add my congratulations as well on the strong quarter. I have two questions. The first is, how would you describe the number and the average deal size of potential displacements of competing vector databases within your pipeline. And are you baking in any uptick in vector database displacements in your Q4 guide?

Ashutosh Kulkarni: Yes. Let me maybe touch upon that. So, whenever we displace an incumbent, it just depends upon the kind of workload where things were in terms of the implementation, and with a lot of the vector database situations, these tend to be, if we display somebody, that implementation is not likely to be very massive because GenAI is relatively young to begin with. So we are not baking in anything specific related to that. Our entire focus when it comes to GenAI is to win as many deals as possible, right? That’s why we focus on land, the 1,750 customers on Elastic Cloud that are using us for GenAI, that’s where customers are baking us. There’s a design win that we are getting. They’re baking us into their design. That’s something that we really focus on, and then getting those commitments, getting them to start to implement is really, really important.

I’m not looking at the market is so young in a way and there is so much opportunity that the focus in this area is not necessarily on displacements. We’ll often displace somebody that might have been selected by the customer earlier, but that’s more just a situational thing as opposed to a strategy.

Howard Ma: Okay. That makes sense. Thanks, Ash. And as a follow-up for Eric, can you help us understand what caused the sequential growth decline in the other subscription revenue line? Is there anything to call out in terms of renewal timing that could impact this line in Q4, and more broadly, just how we should think about the sustainable growth rate of the self-managed business? Thanks.

Eric Prengel: Yes. Thanks for the question. I really appreciate it. As we think about the self-managed and cloud business, we’re actually pleased with the growth that we saw in both of them, and of course, there are some variances here and there, but we thought it was a strong performance from both of them and that came in the guise of both the commitments that we saw, which were strong in Q3 as well as the consumption that we saw. So overall, we’re very happy with both the self-managed — with the other subscription and the cloud business. If you think about it — I was just going to say one more thing, sorry, as you just think about those businesses in Q4, we’re guiding to $380 million at the midpoint, so there’s not a lot of moving parts between self-managed and the cloud.

And the reason where — our guidance is where it is, is a couple of reasons. You’ve got three less days in Q4 relative to Q1 to Q3, and that’s about a $10 million headwind on a sequential basis. And there’s also about $1 million to $2 million of FX impact. So as you think about the different moving pieces, there’s not a ton of variation expected.

Howard Ma: Okay. Thank you.

Operator: The next question will come from Koji Ikeda with Bank of America. Please go ahead.

Koji Ikeda: Hey, guys. Thanks so much for taking the question. Maybe just one from me in the interest of time. A question for you, Ash. And I recall we had a conversation a couple of months ago about customers that were seeing multiples of ACV uplift when adopting certain AI features from Elastic, which can be great from a revenue perspective, but maybe not so much from a long-term customer cost perspective. So I guess the question here is how much of the revenue upside was driven by bursting ACV from customers, adopting AI features and how are you managing the long-term value proposition for your customers?

Ashutosh Kulkarni: Yes, it’s a great question. You know, let me — the AI area for us is young enough that if you think about the revenue performance and so on, like I wouldn’t correlate it to that. The strength in our revenue was pretty broad-based, like I mentioned, Koji. The point that you called out, this is something that I’ve talked about in the past. It’s really important for us to continue to add functionality that brings down the cost over time for people to do things in a much more efficient way. And that’s true not just in AI, but across the board. And with AI, what it does is it just motivates more and more workloads to come to Elastic. The capabilities like better binary quantization that we introduced that allows somebody to store these vector embeddings in a much more efficient way and do their Gen AI, their RAG retrievals in a much more efficient way.

That is one of the reasons, one of the many reasons why those kinds of features are why we are winning the kinds of success that we are winning. That’s why customers are increasingly choosing us as the platform of choice for building runtime AI applications. And our focus is on continually doing that because the more we can win these workloads, the bigger a role that we can play in the whole AI ecosystem over time and that’s going to be the key to long-term success. So we’re going to keep doing that and we’re going to keep managing it. And because it’s early enough, right now, it’s — there is no factor there that’s affecting revenue per se.

Koji Ikeda: Thanks, Ash. Nice quarter, guys. Thank you so much.

Ashutosh Kulkarni: Thank you.

Operator: The next question will come from Michael Cikos with Needham and Company. Please go ahead.

Michael Cikos: Hey, guys. Thanks for taking the questions here. I wanted to cycle back. I believe it was Rob Owens who was asking about the customer count. And I just wanted to get a better understanding. I would have thought that the customer count in some way would be benefiting from industry M&A out there. So is the — are you guys benefiting from industry M&A at this point and maybe is it more mixed because previous — customers who were previously dual sourcing their solution are now bringing more of their estate to you. Like how do we think about how industry M&A might be benefiting you guys where we sit today?

Ashutosh Kulkarni: Yes. So if you think about the total customer adds, in the past, a lot of it has, has also come from the SMB side, if you will. And the SMB segment has been generally flat like we’ve talked about for many quarters now. And our focus really is on the enterprise and mid-market customers. That’s where we are really driving our energy, our sales-driven motion is all there. And in that segment, we obviously, like we’ve talked about in the past, are seeing the benefit of customers wanting to consolidate onto our platform because some of the incumbents that either because of M&A reasons or other factors are starting to fall behind on the capabilities that they’re delivering, on the innovation that they’re driving and it’s just becoming a greater and greater reason for customers to look for alternatives like Elastic and we are definitely seeing the benefit of that.

Michael Cikos: And so if that’s the case, is it fair to think, hey, existing customer, Mike Cikos is already using Elastic for search and the consolidation takes place, but it’s not necessarily going to benefit that customer count because I was already with you in the first place. Is that a fair conclusion from what I’m hearing?

Ashutosh Kulkarni: Exactly, exactly, because a lot of it ends up being effectively expansions, right. It’s new workloads that are coming on to Elastic. And if you just think about that cohort of enterprise and high propensity mid-market customers, many of them are already customers of Elastic. And that’s not — it’s not a numbers game in that area, right. It’s not the long-tail of small customers. That’s not where our focus is. It’s on those larger customers, many of them have existing relationships with us and they just add more workloads. If they were a search user, now they might be adding us for security or for observability or vice versa. And that’s what’s driving the expansion. And that motion is working very well for us.

Michael Cikos: Very helpful. Thanks, Ash. I’ll keep the two questions. Thank you, and congrats.

Ashutosh Kulkarni: Thank you.

Operator: Your next question will come from Kash Rangan with Goldman Sachs. Please go ahead.

Kash Rangan: Hey, thank you very much. Congrats on the quarter. Ash, I’m just curious to get your perspective on the rollout of generative AI. If it moves from training to post-training and inference, how does the opportunity set change or not change for Elastic? Thank you so much.

Ashutosh Kulkarni: Yes. So where we play in, Kash, in the whole ecosystem is when customers are deploying their inference models and other things in an environment where they’re building these Gen AI applications and need retrieval. And pretty much anything that you do, whether it’s semantic search or building of conversational apps or building these agentic workflows, as long as you are doing it for the purpose of providing some connection to an organization’s data, you are going to need retrieval. You’re going to need a retrieval-augmented generation model and that’s where we come in. So all of these phases of different types of agentic applications, it just increases our TAM. It increases our TAM, it increases the total — the amount of cycles that somebody spends on our platform because these ML jobs tend to be more intensive and that’s the benefit, which is why we are so focused on the whole AI area.

Kash Rangan: Got it. And in this world, that’s fascinating, as we move into agentic applications being deployed at runtime or inference time, how does Elastic differentiate in that marketplace where you have companies like MongoDB and others that are likely to embed RAG capabilities in their architecture. What is the unique proposition that Elastic will have at that point in time? Thank you so much and that’s it from me.

Ashutosh Kulkarni: Yes, great question, Kash. So, it’s really important to be a complete platform. And you are seeing that others are now trying to catch up with where we have been for some time. We saw this very early on, which is why over four years ago, we invested in building our own vector database. And since then, you’ve seen that we also invested in building our own embedding models, in building our re-ranking model. We’ve built things like our playground for evaluation and so on. There’s so much functionality that we’ve delivered that not only has this — at the center of it all, this very, very efficient vector database, but then everything else that you need to build a Gen AI application soup-to-nuts and we give you the choice to connect with whatever large language inference model you want to connect to, whether that is OpenAI or Anthropic or Cohere or even if you want to use something that’s open-source based, right.

You’re seeing the tremendous amount of innovation in open-source. So that’s why our platform is as popular as it is because we are way ahead in terms of the functionality, just how efficient and scalable and complete our platform is for this kind of purpose. So, we intend to keep racing ahead and being ahead of the pack.

Kash Rangan: Wonderful. Thank you so much.

Operator: The next question will come from Andrew Nowinski with Wells Fargo. Please go ahead.

Andrew Nowinski: Thank you. I wanted to ask a question on the 100,000 plus customers. So it looks like you it looks like Gen AI added about 30 out of the 40 large new customers. And I’m wondering, are those existing customers that brought on a new Gen AI workload and subsequently pushed their spend to over 100,000. Are those new customers coming to Elastic and they’re just starting at a much larger scale than your non-Gen AI customers?

Ashutosh Kulkarni: Thanks, Andrew. And just to clarify that a little bit, as you think about that 270 customers who are using Gen AI, who are 100K plus customers at Elastic, it doesn’t necessarily mean that those are new customers. It could be that they’re new to Gen AI. So if you think about the population of 1,460 customers and we added about 40 relative to last quarter, the 30 or so that were added that are specific to GenAI don’t have — the 40 and the 30 are not necessarily aligned. It could be that those 30 were a subset of the 1,460. But I think what you’re getting it, and what I think is really important, is that we are seeing significant traction with GenAI across-the-board and with our larger customers using it. We talked — Ash talked about those $5 million-plus customers that we landed in GenAI and the three that we landed last quarter, so clearly, we’re seeing a lot of momentum with people adopting GenAI, both who are already used to Elastic and now they’re adding GenAI to their use cases and also with some of these new use cases from customers where they’re adding GenAI.

So overall, it’s been a strong tailwind to the business.

Andrew Nowinski: Okay. Thank you. And then as it relates to those GenAI customers, do you see the cross-sell opportunity to sell them Observability as a higher percentage maybe versus a non-GenAI customer just given that how much they’ve invested in these GenAI workloads? I would think they’d want to monitor those more so than maybe any other workloads they have in their environment. And that’s it from me. Thanks.

Ashutosh Kulkarni: Yes, that’s a great question. And I don’t know if GenAI applications are deserving of more monitoring or not, at the end of the day, Andrew, the way most customers look at it is, they think about the application. If it’s an important application, they want to make sure that they monitor it, so they can ensure its uptime, they can detect failure conditions quickly, and from our perspective, our focus is always on cross-selling and upselling, right? Like we’ve talked about the land and expand motion. So if we talk to a customer about building a RAG app-based application and they use us as their vector database and more, we’ll absolutely talk to them about, hey, how can we help you in terms of monitoring it? How can we help you in terms of securing?

And just the fact that we are having a much more strategic conversation with them allows us to open more doors with all of our solutions. So we do that all the time. I don’t know if GenAI necessarily drives it more than others, but it’s definitely a nice momentum for us.

Andrew Nowinski: Thanks, Ash.

Operator: The next question will come from Jake Roberge with William Blair. Please go ahead.

Jake Roberge: Yes, thanks for taking the questions. Ash, it sounds like the go-to-market transition is going pretty smoothly at this point, what were some of the changes that you were able to make to really stabilize that motion after Q1? And how are you thinking about the opportunity that new model unlocks for you moving forward?

Ashutosh Kulkarni: Yes, it’s a great question. So the thing that we really double down on was the focus with which we were managing the pipeline and the pipeline progression, you know, the metrics that we look at is pipeline getting created at the right pace that we have been used to in the past and is it progressing at the same pace that it used to in the past, and that extra inspection, the effort that we put into it is now sort of part of what we do on a regular basis and the goal is to continue driving that. So that’s what’s allowed us to recover as quickly as we have, and I feel really good about where we are. Now, in terms of the benefits of the changes that we had made to begin with, you know, a lot of the changes were about creating greater focus on our highest propensity customers, both in enterprise and in mid-market, and that is allowing us to effectively have better conversations, richer conversations with customers and grow the deals in a much nicer way.

And one data point that I’m particularly pleased about is the fact that in the first three quarters of this year, we’ve already closed more million-dollar deals than — sorry, we’ve added more million-dollar customers than we did in all of FY ‘24. So to me, that’s a really good sign about how our expand motion is working. And these are good sort of early data points of what we can continue to do as we focus on our execution.

Jacob Roberge: That’s helpful. And then I know you recently moved the licensing model back to more of an open source model, can you talk about how that shift has impacted recent top-of-funnel activity, especially as it relates to the vector search and database opportunity?

Ashutosh Kulkarni: Yes, it’s still really early, but what I’ll say is the change — the reason for the change was because we wanted to make sure that we are visible and discoverable in all the places where developers go to find open source options for various technologies, and — because we didn’t have an OSI compliant license until we adopted the GPL license a couple of quarters ago, that kept us out of some of those places. So that has been a big reason why we did it. And just the level of excitement to the community suggests that we are on the right path, we are on the right track. So in the overall open source world, these kinds of payoffs happen over a period of time, but I’m very excited about what this means because the more customers adopt our vector database today, the more the opportunity for us to continue to drive this business with the tailwind of Gen AI for many years to come.

Jacob Roberge: Thanks for taking my questions.

Operator: The next question will come from Andrew Sherman with TD Cowen. Please go ahead.

Andrew Sherman: Great. Thanks. Thanks for squeezing me in. Congrats on the quarter. Eric, maybe just — Ash and Eric, sales and marketing growth of 9% was — it’s below revenue growth clearly, and the headcount adds sequentially were a bit down versus the past couple of quarters. Maybe just talk about where you stand from a sales capacity standpoint as you close out this year and head into next year. How do you make sure you have enough capacity to keep this level of revenue growth higher? Thanks.

Eric Prengel: Yes, it’s a great question and one that’s particularly relevant given that we saw Q2 and Q3 were strong quarters. We’re happy with the way the field is executing and it gives us confidence to continue to invest in the business. We talked a little bit about it in the prepared remarks, but we do plan on investing in the business as we get into FY ‘26. And as we think about those investments, we expect that they’re going to come in the field as well as marketing and product. They’re all places we can grow. And so field capacity is something that we actively monitor and track. We track it almost as closely as we track our pipeline. We know that it’s going to drive our growth and it’s something that’s important. We’re still hiring heads into the field in Q4. But overall, the way you should feel is that we feel comfortable with the headcount we have and that we need to drive FY ‘26.

Andrew Sherman: Great. Thank you.

Operator: The next question will come from Shrenik Kothari with Robert Baird. Please go ahead.

Shrenik Kothari: Hey, thanks for taking my question, and congrats for the great quarter. Hey, Ash, so you mentioned the advanced AI features, you mentioned logsdp Index Mode, Rerank, Vector Search are driving upgrades from lower-tier subscription to enterprise-tier and it’s not all kind of consumption and expansion driven? Can you provide any insights into how these up-tier expansions you’re seeing, especially this quarter over the last few quarters compared to some of the historical rates, and between AI Observability functionalities, could you help us unpack that? What are the most consistent catalysts for customers moving up the tiering? And then I had a follow-up for Eric, yes.

Ashutosh Kulkarni: Yes, that’s a great question. The motion for us has consistently been to grow along a few vectors. One is, obviously, as more data grows, like — that drives more consumption, so we grow with that. The second is to get more workloads onto our platform. So that’s the expand motion where we are always, you know, talking to customers about how they can use us for additional different kinds of use cases. We’ve talked about that on this call. And the third, like you talked about here, is getting customers to higher tiers, and the motion to get customers to the enterprise-tier has been something that’s worked really, really well for us even in the past. And they don’t normally upgrade to a higher-tier just for one feature, right?

There are all kinds of different interesting capabilities that we have in the product that encourage customers to step up to higher tiers. Searchable Snapshots is a perfect example. That was a big driver. The logsdb Index Mode that you mentioned that we just came out with recently, we feel really good about that. That’s going to be another feature that we believe is going to drive similar kinds of upgrades. And then for all the AI functionality, whether it’s their AI assistance or attack discovery or for even things like our ML nodes and so on, all of those have been areas that have convinced customers to move up to higher tiers. So it’s not one thing, but it’s this combination, and our goal is to always give customers more reasons to move up.

Shrenik Kothari: Got it. And just a quick follow-up, Ash, and Eric can chime in. On the segmentation changes, the go-to-market, right, have those affected the timelines for these up-tier transitions compared to trends or have you established any kind of internal success metrics, incentives, comp structuring around that, which helps kind of drive faster up-tiering. Are you seeing that?

Ashutosh Kulkarni: Yes. The way I think about it is, it’s something that we put into place in Q1 and it took, obviously, we had some issues with our execution in Q1 as we’re going through the transition. But as we’ve gone through the transition, I think that we’ve been happy with what we saw in Q2 and Q3. And the incentives that our people have is really to focus on enterprise and commercial, and that’s where our business is focused. We’ve talked about it a lot and that’s the part of the customer segmentation that we’re focused on. And we think that we’ve done a really good job with that based on the incentive structure that we have for our reps.

Shrenik Kothari: Got it. Great. Thanks a lot, Ash, Eric. Appreciate it.

Operator: The last question will come from Joel Fishbein with Truist Securities. Please go ahead.

Joel Fishbein: Thanks for squeezing me in. You, Eric, you’ve touched on this a few times, but I really wanted to hone in a little bit on Q4 renewals. Can you just remind us how big the renewal cohort is in 4Q, and with your — it seems like your capacity is there and the pipelines are there. So I’d just love to get a little bit more color around that, that’d be helpful.

Eric Prengel: Yes, the way I think about it is actually this is a good time to mention this in Q4 — we’re not going to give specific color around the dollars of renewals or otherwise. But one thing that’s important to note is that as you recall from Q4 ’24, there was about $15 million of pull-forward business that was higher than seasonally normal. And so it’s not specific to this topic, but there were $15 million that pulled forward. And as you think about that and the year-on-year compare, we’re probably not going to see that same volume of pull-forward in Q4. And so that’s something just to call out as I know a lot of people look at some of the metrics that are either balance sheet or backlog metrics. But we continue throughout the year, our renewal rates have stayed where you’d think they would have and we’re happy with that.

Just generally giving you a sense of how we’re modeling Q4, there’s still going to be a slight overhang from the commitments that were a shortfall in Q1. We talked about the three-day headwind and now that’s about a $10 million headwind total. And as you compare with last year FY ’24, it’s about a one — it is one day less in FY ’25 because we don’t have the leap year and so that’s about a 1% headwind. There’s also $1 million to $2 million on FX and we’ve talked about how we’re modeling consumption and given that we saw a few larger customers drive an acceleration in consumption that we don’t necessarily expect in Q4, we’re not modeling that in our guidance.

Shrenik Kothari: Okay. But is there a pretty big large customer renewal in 4Q?

Eric Prengel: There’s nothing that’s out of whack abnormal with what we’d normally see in the fourth quarter of any year.

Joel Fishbein: All right. Thank you for the clarification.

Eric Prengel: Yes, of course.

Operator: This concludes our question-and-answer session. I would like to turn the conference back over to Ash Kulkarni for any closing remarks. Please go ahead.

Ashutosh Kulkarni: All right. Thank you all for joining us today. I’m excited to welcome Navam as our CFO for this next phase of our growth. I’m encouraged by the continued strong momentum across all aspects of our business and we look forward to giving you an update next quarter. Thank you all.

Operator: The conference has now concluded. Thank you for attending today’s presentation. You may now disconnect.