Elastic N.V. (NYSE:ESTC) Q1 2026 Earnings Call Transcript

Elastic N.V. (NYSE:ESTC) Q1 2026 Earnings Call Transcript August 28, 2025

Elastic N.V. misses on earnings expectations. Reported EPS is $-0.23 EPS, expectations were $0.42.

Operator: Good day, and welcome to the Elastic N.V. First Quarter Fiscal 2026 Earnings Results Conference Call. [Operator Instructions] Please note this event is being recorded. I would now like to turn the conference over to Eric Prengel, Global Vice President of Finance. Please go ahead.

Eric Prengel: Good afternoon and thank you for joining us on today’s conference call to discuss Elastic’s first quarter fiscal 2026 Financial Results. My name is Eric Prengel, Global Vice President of Finance. On the call, we have Ash Kulkarni, Chief Executive Officer; and Navam Welihinda, Chief Financial Officer. Following their prepared remarks, we will take questions. Our press release was issued today after market close 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, our expectations regarding the demand for 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.

Unless specifically noted otherwise, all results and comparisons are on a fiscal year-over- year basis. The webcast replay of this call will be available on our company website under the Investor Relations link. Our second quarter fiscal 2026 quiet period begins at the close of business on Friday, October 17. We will be participating in Citi’s Global TMT Conference on September 4, the Goldman Sachs Communacopia and Technology Conference on September 8 and the Piper Sandler Growth Frontiers Conference on September 11. Finally, Elastic will host a Financial Analyst Day in combination with our New York City ElasticON event on October 9, and we hope many of you will join us in person. With that, I’ll turn it over to Ash.

Ashutosh Kulkarni: Thank you, Eric, and thank you all for joining us today. Elastic had an excellent Q1 and a strong start to the fiscal year, delivering 20% revenue growth for the first quarter, surpassing the high end of our guidance. Sales-led subscription revenue, calculated as subscription revenue, excluding monthly Elastic Cloud, grew by 22% and was driven by strength in both our cloud and self-managed offerings. Our growth was supported by the ongoing demand for our highly differentiated search AI platform and our sales team’s solid execution. The inherent leverage in our business model and our disciplined execution continue to fuel our profitability, resulting in a non-GAAP operating margin of 16%. We ended the quarter with more than 1,550 customers spending over $100,000 as enterprises continue to choose Elastic for their search, observability and security needs.

Amidst today’s rapidly changing global landscape and with AI now clearly shaping technology decisions, our Q1 performance directly demonstrates the value that the Elasticsearch AI platform delivers to customers. Market demand for our solutions has strengthened, contributing to our overall success this quarter. Our strong market position is further deepened by the operational strength of our sales team with the territory changes we made now fully benefiting our execution. Our go-to-market momentum is building across the board. In the U.S. public sector, we are seeing signs of stabilization. In U.S. public sector win from the quarter, an intelligence agency adopted Elasticsearch and Observability for their AI-powered enterprise services, consolidating on to Elastic due to our reputation as a trusted mission partner and owing to the strength of our AI capabilities.

Our strategic agreement with the U.S. General Services Administration, or GSA, which we signed in Q1 and ongoing progress on FedRAMP high certification for Elastic Cloud are helping build positive momentum. Both initiatives are boosting interest among U.S. civilian and defense agencies who aim to modernize with scalable, productive and efficient technology. With our sales team fully primed for this environment, we are well-positioned to execute and capitalize on the federal government’s efforts to digitally transform and advance its infrastructure with our innovative platform. A year ago, we revamped our sales segmentation model to build for the future, focusing our team on expanding enterprise accounts and landing high-potential mid-market customers, measures which are proving very effective today.

This tactical alignment continues to drive progress in our strategic segment, where we enable generative AI application development and consolidation for our largest customers. For example, a global professional services organization expanded their commitment by choosing to migrate to Elastic Cloud in Q1. They rely on Elasticsearch as their vector database to power 40 different internal and client-facing applications. The transition to Elastic Cloud will enable them to achieve greater operational efficiencies and seamlessly access our more advanced search features. Critically, as they advance their gen AI initiatives for clients, Elastic’s advanced search technology will be instrumental in unlocking insights from unstructured data at scale.

In Q1, we saw significant activity around gen AI with many customers choosing Elastic as a runtime platform for building gen AI applications using our vector database, embedding and reranking models, MCP server and other platform capabilities for building conversational AI and agentic applications. Now over 2,200 Elastic Cloud customers are using Elastic for gen AI use cases with over 330 of these customers spending $100,000 or more annually. In Q1, we added more million ACV Elastic Cloud customers using Elastic for gen AI use cases than the prior 2 quarters combined. We are also excited to witness AI-native businesses being built on Elastic to introduce entirely new business models. In Q1, an AI-native music company expanded their use of Elasticsearch, upgrading from a monthly cloud subscription to an annual agreement as they see growing adoption of their applications.

They leverage Elastic to manage vast amounts of song data, supporting full text and semantic search for millions of users as they continue to grow and launch new products. The company chose our Search AI technology for its performance, speed and ability to scale alongside their rapid growth, which in turn drives their Elastic consumption. Our customers’ requirements for speed, scale and relevance drives our continued investment in product features to ensure that every query happens in real time with accuracy and reliability. This quarter, we launched new capabilities to improve performance and cost efficiency of our vector database, now making our Better Binary Quantization or BBQ and ACORN-1, a smart filtering algorithm, available to all users by default.

BBQ and vector search with ACORN-1 helped us land a 7-figure expansion deal with a global wholesale provider of machinery parts for Elasticsearch and observability. They rely on Elastic to drive their e-commerce platform, which consists of over 1 million stock items and a database of nearly 50 million SKUs. The retailer is implementing a hybrid search system, which requires a platform capable of interpreting natural language queries and performing exact and semantic matches to deliver more accurate and relevant search results. They chose Elastic due to our extensive experience in retail search transformation and our customizable search AI functionalities, all within one platform. AI is reshaping the software stack and LLMs are becoming the new operating system for defining business logic.

In the past, most software relied on data and data platforms optimized for structured data. Today, LLMs operate on all data and need a data platform optimized for all forms of data, structured and unstructured, text in spoken and programming languages, audio, video, graphs, vectors and more. Elastic is the world’s leading vector database. Crucially, our continued leadership stems from the foresight that what matters most is relevance in data retrieval, irrespective of the language, type and messiness of the data. When you get relevance right, you provide accurate context to LLMs to do their job, and this accuracy matters even more as Agentic AI gets used for automating increasingly more complex business tasks. With Elasticsearch, relevance is our true competitive advantage, fortifying a defensible moat around our business.

As enterprises build more agents and develop software in new ways, the importance of getting context and search relevance right will only grow. This is why we have invested for years in developing our own embedding models, reranker models, data chunking strategies and more, all with the goal of being the absolute best at search relevance. It is this innovation that gives us the confidence to be the leading data retrieval and context engineering platform for the AI era. This also forms our asymmetric advantage in the other markets we play in, including observability and security. In anchoring our observability and security solutions on Elasticsearch, we fuse the immense power of Search AI into both and automate the observability and security processes of our users with our AI capabilities like attack discovery, auto import and our AI assistance for observability and security.

It is precisely these advanced capabilities that contributed to our security business achieving strong results this quarter. As AI reshapes the SIEM landscape, Elastic Security unifies SIEM and XDR into a single AI-powered platform, extending protection across customers’ data infrastructure and eliminating the need for multiple stand-alone tools. In Q1, 1/3 of our new and expansion wins in security involved competitive displacements. In one such deal from the quarter, one of the largest integrated academic health systems in the U.S. selected Elastic Security to replace its existing SIEM solution. This 7-figure expansion deal marks the customer making a strategic shift from an incumbent solution towards a more scalable AI-driven security approach, driven by their need for a flexible platform to unify data.

Elastic stood out due to our ability to support a broad set of data sources and our market-leading AI features, including attack discovery, demonstrating our leadership in defining the future of SIEM. Our consistent vision of solving security as a data problem while driving innovation in AI positions Elastic at the forefront of the market. In doing so, we are being rightly recognized by independent research, and we are delighted that Elastic has been named a leader in the Forrester Wave: Security Analytics Platform in Q1. Our promise in security is further demonstrated by Elastic Security’s 100% score in AV Comparatives Business Security test for endpoint security, where we were the sole participant among 17 vendors to achieve a perfect score in both the real-world protection and malware protection tests.

In pairing Elastic anti-malware prevention with our ransomware defense and leading SIEM features, we achieved world-class XDR. And our innovation has not stopped. Earlier this month, we introduced the Elastic AI SOC Engine or EASE. Many SOC teams today rely on SIEM and endpoint detection and response or EDR, solutions that generate valuable alerts but lack mature built-in AI capabilities to conduct investigations. EASE integrates with existing SIEM and EDR platforms to connect our advanced AI tools into their environment, allowing for AI-powered alert correlation with attack discovery and access to our AI assistant. Architected as an agentless integration on top of a customer’s existing stack, EASE is an on-ramp to Elastic Security. This commitment to AI-driven innovation extends beyond security.

Our AI capabilities and powerful analytics also earned us recognition as a leader in the 2025 Gartner Magic Quadrant for Observability Platforms for the second year in a row. Elastic’s leadership reflects how we are transforming observability from a reactive tool into a solution for real-time investigations through the power of our Search AI platform. We are shipping new tools like EASE and our recently announced Logs Essentials, a new low-price tier of Elastic Observability within Elastic Cloud Serverless for customers wanting a fully managed offering. Serverless is now generally available on all 3 cloud hyperscalers, including on Microsoft Azure. Serverless is gaining traction with contributions surpassing our Q1 targets as more customers adopt this deployment.

The Elasticsearch AI platform meets customers where they are with deployment options for cloud, hosted and serverless and self-managed environments. This quarter, I visited India, Australia, Singapore and Japan to meet with customers across numerous industries. Despite vastly different businesses, every conversation I had revealed the common desire to do more with their data. Enterprises are all looking to leverage their information more effectively. This consistent feedback reinforces the universal need for powerful data solutions like ours, especially one that is optimized to address the need for search relevance and context in an LLM- centric world. In closing, Q1 was an outstanding quarter, fueled by focused execution and strong demand.

Our platform is more differentiated than ever, providing us a competitive advantage in gen AI and platform consolidation across all industries. We have the ability to win in every market where we are playing, and I’m excited to see our progress unfold. This quarter’s performance highlights the talent and dedication of our team. Navam and I are truly grateful for the continuous hard work Elasticians put in daily. Thank you as well to our customers, partners and investors for their ongoing support and trust. I’ll now turn it over to Navam to review our financial results in more detail.

Navam Welihinda: Thank you, Ash. Q1 was an excellent quarter with solid execution across the business. We exceeded the revenue and profitability metrics we set out to achieve, and our go-to-market team is executing well on all fronts. Our Q1 results provided a promising start to the year. This performance positioned Elastic to enter Q2 and the remainder of fiscal 2026 from a position of strength. Our total revenue in the first quarter was $415 million. We grew 20% as reported and 18% on a constant currency basis. Our sales- led subscription revenue, calculated as subscription revenue, excluding monthly Elastic Cloud, was $339 million, growing 22% as reported and 20% on a constant currency basis. Q1 ’26 marked the fourth consecutive quarter of strong performance since we made the sales segmentation changes last year.

Our sales-led subscription revenue grew 22% in Q2 ’25, 18% in Q3 ’25, 19% in Q4 ’25 and now 22% this quarter. These consistent results demonstrate the durability of our team’s execution. The revenue performance we saw this quarter was broad-based across both our cloud and self-managed environments. We saw strong customer commitments with key wins across all our solution areas. Both generative AI and platform consolidation continue to be powerful tailwinds benefiting search, observability and security. As Ash mentioned, we saw competitive success in security with 1/3 of new and expansion deals in security coming from replacing an incumbent solution. Our traction is further supported by new product releases, including our Elastic AI SOC Engine or EASE, which uses AI to enhance threat detection.

As you heard from Ash, our team continued to operate effectively in all areas, and we saw strength across all our geos. In the U.S. public sector, we’re seeing stabilization and the team is fully primed to execute. Even with ongoing shifts in select civilian agencies, Elastic’s cost-to-value proposition remains a compelling incentive for our public sector customers to consider our products as they look to consolidate mission-critical tools and increase efficiency. Our current remaining performance obligations, or CRPO, which is the portion of RPO that we expect to recognize as revenue within the next 12 months, remains solid. In the end of Q1, CRPO was approximately $956 million and grew 18% year-over-year and 17% in constant currency. CRPO is a useful supplemental measure of commitments when evaluated in conjunction with sales-led subscription revenue.

During the quarter, our $100,000 annual contract value customer count grew approximately 13% year-over-year. representing approximately 180 net new customers over the past 4 quarters. Quarter-over-quarter, we added approximately 40 net new customers and continue to see strong expansion from our existing customer base. Our total customer count reached approximately 21,550 at the end of July. Approximately 80% of our annual recurring revenue comes from $100,000 annual contract value customers. Moving forward, we will only disclose our total customer count annually as this metric does not fully represent our quarterly total revenue performance. On the consumption front, we are happy to see that consumption remains strong. In May, we increased prices on our cloud and self- managed environments and demand for our solutions remains high as we continue to deliver more value to our customers through new product features and functionality.

Now turning to Q1 margins and profitability. I will discuss all measures on a non-GAAP basis. We delivered strong profitability across the board with a gross margin of 79% and an operating margin of 16%. In Q1, we recognized a onetime credit of approximately $4 million related to our cloud infrastructure costs. The credit caused a onetime gross margin benefit of 1%. Additional margin expansion is representative of the inherent leverage in our model. Our disciplined approach to costs, combined with increasing revenue, underpins our strong profitability, further supported by our cash generation. In Q1, we achieved an adjusted free cash flow margin of 28%. Historically, we experienced quarter-over-quarter seasonality related to the magnitude of the prior quarter’s bookings and the collection of those bookings.

Keeping these fluctuations in mind, we expect Q2 to follow normal seasonal patterns, representing a sequential decline in FCF. We manage and view adjusted free cash flow on a full- year basis and believe we have the potential to maintain and expand our free cash flow margin over time. Now for our outlook for the second quarter and the remainder of fiscal 2026. We are pleased with our strong execution in the quarter and the momentum we’ve built heading into the balance of fiscal 2026. While we continue to operate in a complex macro environment, conditions did not deteriorate to the degree we had factored into our guidance in May. As such, we are raising our fiscal 2026 revenue guidance. Note that our Q2 2026 assumptions factor in benefit from our price increase, which I discussed earlier.

We do not formally guide to adjusted free cash flow. Still for fiscal 2026, we expect to sustain the level of adjusted free cash flow margins that we achieved in fiscal 2025. With these assumptions in mind, for the second quarter of fiscal 2026, we expect total revenue in the range of $415 million to $417 million, representing 14% growth at the midpoint or 14% constant currency growth at the midpoint. We expect non-GAAP operating margin to be approximately 16%. We expect non-GAAP diluted earnings per share in the range of $0.56 to $0.58, using between $108.5 million and 109.5 million diluted weighted average ordinary shares outstanding. For fiscal 2026, we are raising our total revenue, which improves our expected non-GAAP diluted EPS. We expect total revenue in the range of $1.679 billion to $1.689 billion, representing approximately 14% growth at the midpoint or 13% constant currency growth at the midpoint.

We expect non-GAAP operating margin for the full fiscal 2026 to be approximately 16%. We expect non-GAAP diluted earnings per share in the range of $2.29 to $2.35, using between 109 million and 111 million diluted weighted average ordinary shares outstanding. We will continue to provide updates as we move throughout the year. This quarter’s performance is a testament to the dedication of our team. Ash and I are thankful for the hard work of our employees to deliver these strong results. As a reminder, we are hosting our Financial Analyst Day on October 9 in New York City, where we will showcase the power of the Elasticsearch AI platform and the business opportunity ahead. With that, I’ll open it up for Q&A.

Q&A Session

Operator: [Operator Instructions] The first question comes from Matt Hedberg with RBC Capital Markets.

Matthew George Hedberg: Congrats on the results. Really, really good to see early in the fiscal year. I guess maybe the first one for you, Ash. It was really good to hear about AI relevance with Elastic Cloud and even the progress on serverless thus far. I guess I’m wondering, is there a way to think about what customers — the uplift in customer spend is when they start to think about growing usage of Elastic to support AI. It really does feel like you guys are becoming a bit of a center of gravity for that. But any way to kind of think about what this is doing to customer spend or usage and maybe it becomes even more evident with serverless?

Ashutosh Kulkarni: Yes, Matt, thanks for the question. And like you said, our gen AI momentum is something that we feel really, really good about. The customer adoption has been strong. 2,200 customers in Elastic Cloud now using us for gen AI use cases. What we are seeing is as customers start to use us for all of these AI applications, these workloads tend to be more compute-intensive. And that obviously means that the growth sort of helps. And when we’ve described it as a tailwind, that’s really what it is. Now the extent to which that growth manifests itself, the workload cost depends upon the kind of data, depends upon the kind of use case because these AI computations tend to take up more CPU, tend to take up more memory.

And as you know, our consumption model is biased towards that. So it’s hard to give a precise number, but what we can say is that there is definitely an improvement in sort of the overall consumption that we see as customers use us for AI. Now let me repeat that fundamentally, we are still early in the AI journey. So we are seeing some contribution from AI, but we are very early, and I see a long path here, where by being the core foundation for AI for our customers as they are making multiyear decisions here, this is going to be a tailwind for us for many years to come.

Matthew George Hedberg: Really good to hear. And then maybe just a quick one for Navam. You mentioned the price — the May price increase, which is now reflected in the guide. Is there any way that you could help us think about how that’s benefiting the year? Just any sort of quantification there would be helpful.

Navam Welihinda: Sure thing. Thanks, Matt. So first of all, just starting with Q1, you look at the performance, it was a broad-based overperformance across consumption and across commitments from both our cloud customers and our self-managed customers. When you think about our normal course of business from time to time, we do price increases, and we’ve done one last year for self-managed. We did one this year for self-managed and cloud. The increase in Q1 was mostly related to consumption performance and the goodness of our business. But we did have a benefit from the price increase. And the way you should think about it is a price increase lifts the floor year-over-year. So you get a benefit year- over-year as you think about the growth from year-over-year, but the majority comes from performance rather than price increase.

And then quarter-over-quarter, you’d see a more muted effect of prices as you’ve now got a floor that you will grow from. So that’s how I think about the price increase. Overall, Q1 was, like I said, broad-based from a performance perspective and macro was in a much better spot than where we had originally assumed. So feeling good about the year.

Operator: The next question comes from Koji Ikeda with Bank of America Securities.

Unidentified Analyst: This is George McGreen on for Koji. I really appreciate it. I have one — I wanted to ask on the growth mix. Just understanding, obviously, there’s a lot of momentum with gen AI in search. But if you could maybe stack rank or give us a framework to think about how growth across the business is kind of playing out in observability and security as well?

Ashutosh Kulkarni: Yes, George, thanks for the question. So this was a really strong quarter with a very broad performance strength that we saw across all solution areas. Search, driven by gen AI continues to be a very strong tailwind for us. But this quarter, we also saw security and the platform consolidation motion that we’ve been describing work very, very nicely for us. I think one of the stats that I talked about was the fact that 1/3 of the business in security this quarter came from competitive displacements. And these deals take some time to build, but we are starting to see that momentum. And this is primarily because customers are looking to consolidate onto platforms that tend to see security and observability as a data problem.

And we’ve always done that incredibly well. And as the amount of data, the complexity of data is growing as it’s becoming more and more important to use AI techniques to try and drive automation, even in security and observability, we are seeing our ability to compete and take share really improve, and that’s something that we see as a very exciting thing for the future.

Unidentified Analyst: Appreciate it. And if I could ask another question here. Navam, since you joined, how would you describe maybe the predictability of the model today versus when you joined? Has it changed much? And if so, why?

Navam Welihinda: Yes. Now I’m about 2 quarters in since I joined. I think the big learning for me is on the sales-led subscription side. And I think I mentioned this during my prepared remarks. The execution there and the durability of execution was very strong, right? We had 22% growth a year ago, followed by 18%, 19% and 22% again this year. This is a testament to the consistency of growth we’re seeing from our sales-led motion across both cloud and self-managed. So I’d say that the underlying execution from the team remains very good and very, very — and predictable on the sales-led side. We’re a consumption business, and that’s the one place where there is a little bit of unpredictability on what could happen on a quarter-over- quarter basis. Overall, we had a good quarter in Q1 and given what we expected. So I feel like we have more data now than we did a quarter ago.

Operator: The next question comes from Rob Owens with Piper Sandler.

Robbie David Owens: I really want to drill down on the success that you’re seeing on the security front. I think you said 1/3 of it was coming from competitive displacements. And obviously, we’re seeing a lot of success, I think, across the board from vendors that are competing for this next-generation SIEM opportunity. So I guess relative to the unlock that happened this quarter, was there anything in particular that drove that momentum? Was it more just how the pipeline set up? And as we look forward, maybe what are some of the different key ingredients to further unlock customers that have been with some of those legacy vendors for some time?

Ashutosh Kulkarni: Yes, that’s a great question. And what’s driving that unlock is really a greater and greater appreciation for the fact that security really is a data problem. In the modern landscape today, with attacks getting more and more sophisticated, it is becoming incredibly important to make sure that you’re bringing in all of the data, all of the security-related signals, analyzing all of them, correlating across all of them and then using AI automation to really try and make it easier for the SOC analysts to identify what the issues might be. And the way we think about it is you miss 100% of the threats and attacks in the data that you don’t see. And for that reason, we’ve always had this mentality of thinking of security from a data-first perspective.

Our back end is designed for that. Our AI capabilities are designed for that. And as customers are appreciating this, we are seeing them make multiyear decisions to consolidate onto our platform and that’s driving the momentum. And we are really leaning in. So one of the announcements that we made, the Elastic Security, the AI SOC Engine or EASE, as we call it. What it lets you do is even if you’re using an incumbent different SIEM solution, it allows you to take all of the alerts that might be generated in that solution and then use our AI capabilities to identify attacks within that alert data, which is incredibly powerful because what that means is you don’t have to change your current infrastructure. You can use Elastic on top of it to get significantly more incremental value, and that becomes a stepping stone sort of an on-ramp for customers to then eventually displace, completely take out their existing incumbent and move completely to our solution.

So it’s things like that, that we’ve been working on that give me a lot of confidence on how this is going to progress in the coming years.

Operator: The next question comes from Raimo Lenschow with Barclays.

Raimo Lenschow: Perfect. Congrats from me as well. It’s nice to see the cloud reacceleration, but the bigger upside in my model was actually on self- service. Can you speak to the factors there that drove that reacceleration of growth and what drove that? Was that like you mentioned several times, broad-based, so I take broad-based, but like still there was a very decent step-up on the growth rate there.

Navam Welihinda: Yes. Thank you, Raimo. I’ll take that. Just a reiteration that this is the second quarter now where we had very strong self-managed growth. And the combination of self-managed growth and cloud growth is what we are going for to reinforce our subscription — sales- led subscription revenue, right? That’s the core piece that the company is focused on to drive growth. So the growth in self-managed this quarter was truly, as I mentioned, broad-based. When you think about where it came from geographically, where it came from the solutions, it pretty much most of the — all the geographies and solutions contributed to the self-managed cloud. And that’s sort of the main benefit of it.

Ashutosh Kulkarni: Sorry, I don’t know if you were also referring to self-service cloud or our monthly cloud business, I think that, as you know, it’s generally been trending around the same way. But to Navam’s point, our focus really is on the sales-led subscription revenue, which we are very excited about.

Raimo Lenschow: Yes. Okay. And then Ash, one follow-up is like all the other vendors, like a lot of the other vendors struggling around AI with kind of how to price it properly, et cetera. But you guys have been on consumption for a long time. Like how does that help you at the moment in customer conversations and driving that AI message from you guys forward? Congrats again.

Ashutosh Kulkarni: Thank you. So the reason why consumption as a metric works incredibly well in AI is fundamentally because it makes it very easy for customers to sort of connect the dots between their usage of our platform and the value that they’re getting out of it. So as opposed to a per-user price or something that’s a flat fee, this really is completely dependent on how much of the AI functionality they use. And from our experience, that’s been something that customers really like. As their usage grows, as they get more value from the usage of the platform, they need to pay more and they’re more than happy to pay more. And so we feel that we’ve got exactly the right mix when it comes to the pricing model. And you can see some of that in terms of just the adoption and the growth that we are seeing.

Operator: The next question comes from Mike Cikos with Needham & Co.

Michael Joseph Cikos: Congrats on the strong quarter here. The first question I wanted to ask was for Ash. And coming back, again, I think people are hanging on the 1/3 of the new and expansion wins in security were competitive displacements. But if I could try to drive it that slightly differently. I think all of us are aware of the industry M&A that’s out there. You’re also talking about the sustained execution on the go-to-market front. So I wanted to ask, what is the thought around how durable these competitive displacements are when thinking about what’s taking place on the security front? I think about the amount of time that these deals might be sitting in your pipeline, they might mature. What is the durability for these continuing to convert on a go-forward basis from where we sit today?

Ashutosh Kulkarni: Yes, that’s a great question. And generally, what I’d say is that in the last few years, we’ve been seeing a constant, steady drumbeat, and it’s been growing of customers that are really looking for a change from their incumbent solutions. Most of the incumbent solutions that have been around really thought about SIEM as sort of just the dashboards and the alerts. They didn’t think about the effort that is involved in automating the job of the SOC analyst and things that need to be done to really make it easier to spot the attacks as opposed to just the alerts. And for that reason, we are seeing sort of a secular shift and a migration onto what I would describe as the next generation of SIEM platforms and SIEM technologies that tend to have a bias towards treating security as a data problem.

So we are seeing more and more of these conversations happening. That’s the reason why we introduced capabilities like attack discovery. We introduced capabilities like automatic import, which make it easier for people to migrate their workflows over on to Elastic. And most recently, we introduced our Elastic Security AI SOC engine, so you can get started by using our AI functionality on top of your existing SIEM and making that sort of an easy on-ramp to eventually replace your SIEM provider. We feel very good about this being a tailwind for us for many years to come. And I see this as a really good ongoing motion, and our sales team is leaning into it.

Michael Joseph Cikos: Terrific. And for the follow-up here, just wanted to cycle back to the net expansion rate for a second. Great to hear in Q1 how you guys outperformed across both consumption and commitments, right? I guess, can you help us think about what’s embedded in the guide today for how net expansion is expected to play out over the rest of the year? Are we still assuming relatively stable net expansion? Or are we starting to get an inkling that this might actually begin picking up?

Navam Welihinda: Yes. Thanks for the question, Mike. So look, we had a good start to the year, a great Q1 with going in macro was in a better position than what we thought in the beginning of the year when we issued our first guidance. Consumption was strong and the commitments were strong from our customers. So overall, as you think about where those commitments come from, a lot of it comes from existing customers as they expand usage from us, and that’s driven by our net expansion rate. We don’t guide to future net expansion. But as we think about the full year, what we’ve baked in is more visibility into the year and a better macro situation and also the quarter-over-quarter impacts of price as well as the year-over-year impacts of price have been baked into the guide. We felt good about performance, which is what led to the raise for the full year, and we expect net expansion to perform well over the next several quarters as well.

Operator: The next question comes from Sanjit Singh with Morgan Stanley.

Sanjit Kumar Singh: Congrats on the strong start to the fiscal year. Ash, I wanted to get some help in terms of understanding the impact on some of your most exciting opportunities. And I want to sort of compare and contrast the sort of AI search opportunity, which you guys have been very clear, right? Like we’ve come from POC and evals, initial applications into production and then you have to sort of get — increase the penetration rate in terms of a customer’s overall application real estate to do that long multiyear journey. You guys have been very clear about that. When it comes to the SIEM opportunity, though, is the right way to think about it because it’s a more established category, because there’s a lot of brownfield replacement opportunities. Can that be a more immediate impact on growth in self-managed and cloud growth? I just would love to get your comments on doing the — compare and contrast between those 2 specific opportunities.

Ashutosh Kulkarni: Yes. Thanks for the question, Sanjit. So the way to think about displacements that happen, whether it’s in security or observability, whenever somebody consolidates onto our platform, the first thing to keep in mind is that they have to migrate those workflows over. So typically, that takes a little bit of time. The fastest migrations that we’ve seen happen within a quarter, the longest that we’ve seen take multiple quarters just because there’s actual engineering work involved in moving all of those data streams over. But like you said, these are better understood techniques and these are better understood templates for that. So we have invested a fair bit both from the product side. I talked about automatic import, but also from our services team that has experience and expertise doing these kinds of migrations.

I think the most important thing to think about, though, is we are seeing ourselves as a beneficiary of this wave of migrations and sort of moving to the next generation of SIEM that’s happening within the broad market. And our goal is to take as much of that share as possible. And so I don’t see this as just a onetime thing, but this is, I believe, something that we should benefit from for not just several quarters, but several years to come.

Sanjit Kumar Singh: That’s great color. I had a question on just the federal business, and that was a source of weakness last quarter. It sounds like things are stabilizing. As Fed comes into its fiscal year-end, what are some of the assumptions that you’re baking in for fiscal Q2 and the government’s fiscal year-end coming up next quarter?

Ashutosh Kulkarni: Maybe let me just touch upon that, and then I’ll ask Navam to add to it. The first thing I’d say is we are definitely seeing sort of stabilization in the U.S. public sector. 6 months ago, what we saw was with the new administration settling in with Dodge and everything, like there was a lot of movement. The environment was very dynamic. That has settled. It’s a much more stable environment, and our sales team knows how to execute very well within that environment, especially given that the value that we offer for our platform is incredibly high, and it’s very well received by our customers in the public sector. So we are really excited about that. I will say that Q2 has typically — like we, even in past years, have not seen like a big federal flush or anything of that sort.

So from a public sector standpoint, Q2 hasn’t necessarily been sort of an outlying quarter for us. So just keep that in mind. But let me — I don’t know if Navam, you have anything else to add to that.

Navam Welihinda: No, I think Ash got most of my points. But when we gave our initial guide in May, there was a lot of uncertainty around what would happen with the U.S. public sector, specifically the civilian agencies, would it expand to more of the public sector and the rest of sort of the geos. It clearly did not occur. And the U.S. public sector, while there is some ongoing impacts, have mostly stabilized. And as Ash said, our team is executing well there, and our products are a good fit for what they’re trying to achieve. So we’ve factored that into our second quarter guide. And as Ash mentioned, there’s no real flush that we’re factoring in there, and that’s not something we’d expect.

Operator: The next question comes from Kash Rangan with Goldman Sachs.

Kasthuri Gopalan Rangan: I’ll add my congrats on the quarter. It looks like everything is coming back together for you guys, just the way you would like it. And pardon me, Ash, if this feels like a relax from a few years ago, but I would ask you this, that listen to the call, there is an AI search aspect to it. There’s a security aspect to it. There’s an observability aspect to it. What is it that makes Elastic tick at the end of the day? What is the message to your customer base? Like what is the unifying thread that makes this machine a predictable growth machine that is ready for the next 4 to 5 years?

Ashutosh Kulkarni: That’s a great question, Kash, and that’s the kind of Redux question that I always appreciate. Fundamentally, we think of ourselves as a search AI company. And like I’ve described in the past, our secret sauce is our ability to take in any and all kinds of data, especially messy unstructured data and really get you the most correct, the most relevant information out of it. And as we’ve described in the context of AI, as you think about companies, enterprises, government agencies, what have you, building agentic applications, the criticality of getting the context right is so high, especially as you are building more and more sophisticated agents and that search relevance is absolutely critical. And we are seeing that across the board.

And it’s not just about having a vector database, it’s about so much more than that. So the way we think about our role in this ecosystem is to be that data retrieval and context engineering platform, making it possible to get exactly the accurate context in real time to these large language models. That’s helping us in our search business. But if you then think about security and you think about observability, you really recognize that these are fundamentally at the end of the day, data problems. You’re dealing with complex logs, you’re dealing with complex traces. Application logs are incredibly messy. And if you have to analyze them at scale in real time using AI, we have the best platform for that. So for us, that core search AI piece is the secret sauce.

That’s what’s going to continue to drive our progress and our growth. And that’s why I’m very confident in the long-term growth and strength of our business.

Operator: Our next question comes from Howard Ma with Guggenheim Securities.

Howard Ma: Great. Excellent quarter, guys. I guess building on Kash’s question on use cases, when you analyze your quarterly performance by use case, did growth in search continue to accelerate because I believe that’s been the trend. And part 2 is, as gen AI use cases become more mature, they also require more data to be monitored. So is that leading to more observability cross-sell or not necessarily?

Ashutosh Kulkarni: Yes. So that’s a great question. So what I’d say is that our search business continues to be incredibly strong because of the gen AI tailwinds. And that’s what’s so exciting about what’s happening here. Like I said, this quarter, we also saw a lot of platform consolidation. And in security, I gave some of the examples. Because at the end of the day, our strength in AI is helping us compete better and take more share in observability and security. And that’s the nice part about it. So fundamentally, AI expands the TAM for our search business. And in the other areas, it allows us to compete better. Now to your point about what’s happening overall in the market, we absolutely see that more and more applications, especially these AI-centric applications are being built.

But we are still in the early days. You take any enterprise, you’re talking about a handful or at most dozens of applications and you compare that to the total application landscape that exists in any organization, it’s in the hundreds of thousands. So we are still in the early days. AI has a lot of legs ahead of it. I think this is a multiyear journey where there is a lot of excitement for the future. And the fact that we are getting baked in into the platform, into the infrastructure where our customers are using us as this core context engine just makes me feel very good about the long-term prospects for our business.

Howard Ma: Great. And as a follow-up, you’ve made some significant go-to-market improvements over the last year. It’s a question for Navam. So Navam, you were not at Elastic this time last year, obviously, but when you look at your data on key metrics like sales capacity and productivity and coverage ratios, the number of large deals in the pipeline, so things like that, I’m curious how you would characterize your optimism for the rest of the year versus the stellar quarter you just posted.

Navam Welihinda: Yes. Thanks for the question, Howard. So like I said, I feel good about the year. And the reason I feel good about the year is about the durability of our team’s execution. And that is reinforced by the underlying data we’re seeing in terms of how the sales team has been being able to perform from a subscription revenue less — sorry, a sales-led subscription revenue perspective. And the reason they’re able to do that is they’ve had strong performance from a productivity perspective and our capacity additions are working. So that’s sort of the underlying drivers as to why our sales-led growth has been durable. And we’ve had a great start of the year, and I feel optimistic about the rest of the year.

Operator: The next question comes from Tyler Radke with Citi.

Tyler Maverick Radke: You saw pretty good current RPO bookings this quarter, and you also talked about some pretty impressive $1 million customer adds on AI. Can you just talk about the use cases you’re seeing and sort of what drove that step-up versus the last couple of quarters?

Ashutosh Kulkarni: Yes. Fundamentally, what we are seeing is that our customers are making meaningful commitments to us, Tyler. I think that sales-led motion, as Navam mentioned, has been continuing to do well. On the AI side, it’s an area that we’ve been focused on to make sure that our largest customers, our highest propensity to grow customers are really adopting our AI technology. And as we’ve been driving that, you are seeing some of this momentum. So from my perspective, like my goal is to make sure that every single one of our customers, existing customers and new customers, we lead with our AI functionality. We are getting better and better at it. And my belief is that as more of our customers adopt, as they build more complex applications, these complex applications don’t have just one call to a vector database, but they have like multiple different interactions.

There are multiple moments where they have to do retrieval and context engineering and each of those drives consumption, as you know. So for our consumption-based model, the more we are embedded into every one of their AI applications, the better the traction that we see, and that’s what we are focused on. That’s what we are starting to see.

Tyler Maverick Radke: Great. And a follow-up on the pricing side. I think based on the list price that we saw out there, it looked like the monthly cloud price went up by about 5%. Was that similar across the rest of the business? I think there was price increases on the annual as well as the self-managed side of the equation.

Ashutosh Kulkarni: Yes. So we did a price increase at the beginning of the year. Tyler, as you know, our business model is such that we don’t sell discrete products. So for us, the way as we add more and more functionality from time to time, we will increase our prices. Just to remind you, we did something similar for our self-managed products last year. We had talked about it at the beginning of last year, and we also did a price increase at the beginning of this year, like you mentioned. So for us, this is just the normal course of business to do these from time to time, but it was across both cloud and self-managed.

Operator: The next question comes from Brian Essex with JPMorgan. The next question comes from Brian Essex with JPMorgan.

Brian Lee Essex: Congratulations from me on the strong results. Maybe one for you, Ash. We’re hearing, particularly on the security side, the focus on AI and leveraging enhanced visibility, real-time detection on streaming data, which I think you addressed. But would love to — what we’re also hearing is a focus on more efficient data ingestion, leveraging AI and storage of — more efficient storage of data. And I’m wondering, are you seeing that at all competitively and how you might be positioned to address that need?

Ashutosh Kulkarni: Yes. I mean we have been driving that for many years, right? So one of our greatest strengths is our ability to ingest in massive amounts of data at scale and then store that data incredibly efficiently. So several years ago, we introduced capabilities that allow us to take advantage of object storage, really, really cheap storage and through life cycle management sort of manage how much data you retain on disk versus how much you store in object storage and really bring down the costs of both data storage and data analysis. That’s been one of the biggest drivers for customers to move on to our platform because they see that kind of efficiency gain and that efficiency improvement. Even 2 quarters ago, we introduced a capability called LogsDB that allows you to do even more aggressive data compression and management of log data to store — to bring down the cost of what it takes to store log data.

And these kinds of capabilities are a constant stream of innovations from us. So it’s been a reason why we keep winning, and we are not going to stop on this area. Like we — my firm belief is that given the rate at which data grows, continuing to drive these kinds of innovations is going to be a reason why we’ll continue to win.

Operator: The next question comes from Jake Roberge with William Blair.

Jacob Roberge: Just wanted to follow up on the go-to-market front. You talked about execution improving and the changes starting to bear more fruit. Just in terms of the go forward, where do you see the largest opportunities remaining? And what inning do you feel like we’re in with that overall transition?

Ashutosh Kulkarni: Yes. I mean maybe I’ll address this and then Navam might want to add to it. From our perspective, there is so much opportunity in the enterprise and mid-market segment where our sales teams are focused. The changes in territory alignment that we made, segmentation that we made a little over a year ago, what they were all about was to have our teams more focused on the enterprise and strategic segment and then to go after greenfield territories more effectively. And we are really starting to see the benefits of that. Those are the kinds of changes that are really, really important as you get from $1 million in revenue to $2 million and $3 million and so on. And now we are starting to see the benefit. So we’ve got a long ways to go.

Like I grew up in India, so not much of a baseball player. But what I’d say is that we have the ability to build a true generational company here, keep driving strong growth for many years to come. And our current sales model, our current sales segmentation gives us the ability to continue to do that.

Navam Welihinda: Yes. And I would add to that. I mean we are playing in exceptionally large TAM markets in observability, security and search. And we’re just starting to see AI tailwinds that are taking root in those markets, right? So to Ash’s point, hard to put an inning on it, but it is early days in the journey.

Jacob Roberge: Okay. That’s helpful. And then I know it’s still early, but can you talk about the early feedback you’ve gotten for the new serverless solutions and just how that migration process has been progressing this year?

Ashutosh Kulkarni: Yes. So we obviously have internal milestones that we set for ourselves, and we have been running ahead of those milestones. So that makes me feel really good. The early feedback in terms of the product itself has been really good. Now where we are is, I’ll remind everybody, still pretty early in the overall movement here when it comes to serverless. We are now GA in all 3 hyperscalers, but the total data center footprint that we have for serverless is still relatively small compared to our cloud — Elastic Cloud hosted. Footprint and our goal through this fiscal year is to do the build-out of our serverless and make it available in all the data centers and the majority of the data centers where we do cloud business today.

So as we do that, you will — we continue — we expect to continue to see more and more adoption of serverless because customers prefer to have their data in local data centers, if you will. And in the coming years, I’m very confident that serverless is going to be the primary way in which our customers use Elastic Cloud.

Operator: The next question comes from Brent Thill with Jefferies.

Brent John Thill: Navam, just on the guide, 20% growth in Q1 and guiding the below mid-teen growth or mid-teen growth for the year. I guess that drop-off in the growth, I guess, what are you factoring in? Is it — are there other factors that you’re unclear about that you’re not putting in? Or is it more conservatism? I’m just trying to bridge the great start to the tail off in the growth throughout the year.

Navam Welihinda: Yes, Brent, here’s how I would consume the guide. It was a great start to the year. We had — coming into the year, we’ve laid out the assumptions around the dynamics of macro that we baked into the guide, which led to the low end and the high end of the guide that we gave the last quarter. Clearly, we are in a much more stable macro environment. While it’s still — while there’s still a complex environment out there, it is — it feels much more stable than we anticipated compared to Q1. And you add to that, that there was a broad-based good execution-led Q1 number that came to us this last quarter. So overall, we beat the Q1 number by a good amount, and we raised the full year. And that raise is meant to signify the better position we’re in and the more confidence that we have in the year.

Brent John Thill: Okay. Great. And Ash, maybe I’m mistaken this, but you seem to be pretty excited about the security business. You mentioned it many times. I guess was there something in the quarter that triggered in terms of breadth of transactions, some big deals was there something that maybe — or maybe I’m misreading this in reading into the number of times you mentioned security too much, but just curious if you could pull that thread.

Ashutosh Kulkarni: I wouldn’t call out — obviously, in any given quarter, there are — the deal flow, there might be more deals in one solution area versus another. That kind of happens from quarter-to-quarter. What I’d say is that my enthusiasm in security has been high for a while now. We’ve been seeing a lot of traction with customers moving on to our platform, consolidating onto our platform. We’ve been doing competitive displacements for some time. One of the things to be aware of is competitive displacements like these deals take time. It’s not a 1- to 2-quarter motion, it typically takes several quarters. But that’s also why we’ve been investing in capabilities like automatic import. We recently announced our AI SOC engine that can be used on top of other SIEM products.

So we are doing a lot to make it easier for customers to make that migration journey as easy as possible. So I expect that the momentum that we are seeing on the security side is one that will continue to build over time. And I feel really, really good about it. And if there was just a higher count this quarter, it was just because I’m truly, truly excited about the business across the board.

Operator: Our last question comes from Patrick Colville with Scotiabank.

Patrick Edwin Ronald Colville: I guess I just want to circle back to the price increase because in our field work heading into the quarter, what we were picking up was it was about a 5% price increase across cloud and self-managed. And so I guess, is that quantum roughly right? Does it apply to all customers? And if we exclude the price increase, is that like to work out an underlying number, is that logic correct? Or should we not be thinking about the business that way?

Navam Welihinda: Yes. I’d start off by sort of thinking about the business slightly differently, which is from time to time, the business increases prices. This is something we did last year, and it’s somewhat ordinary course of business as we add more features to our product. And to Ash’s point earlier, we don’t have distinct SKUs. We just add more functionality to the product, and that leads to a more valuable product to our customers. And we reflect that by from time to time evaluating prices and increasing as necessary. There’s discounting that factors in as well. So you can’t really say, hey, it was an x percent increase across the board on every customer. But roughly, that quantum would be on the rough order of magnitude accurate as you portray it.

Now how it relates to the performance, as you think about it is price increases offer a durable baseline that you grow from. So as you go from 1 year to the next, you’re almost — you’re lifting that baseline that you’ll grow from there. So you’ll see a year-over-year benefit. But quarter-over-quarter, you’re just going to see a normal benefit and not something that’s related to prices. So that’s how you should think about price increases. The Q1 performance, like I said, was broad-based. So while we did have benefits to price increase and price increase is something we do from time to time, a lot of the performance — in fact, the majority of the performance came from good solid execution and good consumption from our customers.

Patrick Edwin Ronald Colville: Congrats on a strong start to fiscal first quarter.

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: Thank you and thank you all for joining us today. I’m extremely proud of our excellent results and more excited than ever about the opportunity ahead as we build a generational company. Thank you.

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