Good afternoon, and welcome to the Elastic first quarter fiscal 2027 earnings results conference call. All participants will be in listen-only mode. Should you need assistance, please signal a conference specialist by pressing the star key followed by zero. After today's presentation, there will be an opportunity to ask questions. To ask a question, you may press star, then one on your telephone keypad. To withdraw your question, please press star, then two. Please note, this event is being recorded. I would now like to turn the conference over to Alex Kurtz, Vice President of Investor Relations. Please go ahead. Good afternoon, and thank you for joining us on today's conference call to discuss Elastic's first quarter fiscal 2027 financial results. On the call, we have Ash Kulkarni, Chief Executive Officer, and Navam Welihinda, Chief Financial Officer. Following the prepared remarks, we will take questions. Our press release was issued today after the close of the market and is posted on our website. Slides, which are supplemental to the call, can also be found on 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 on 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 the slides. Unless specifically noted otherwise, all results and comparisons are on a fiscal year-over-year basis. Webcast replay of this call will be available on our company website under the Investor Relations link. Our second quarter fiscal 2027 quiet period begins at the close of business on Friday, October 16th, 2026. We will be hosting a virtual public webinar highlighting our improved metrics capability on September 22nd at 8:00 A.M. Pacific Coast Time, which will be made available on our IR website for viewing. See the Elastic Investor Relations website for more details. With that, I will turn it over to Ash. Thank you, Alex. Good afternoon, everyone. Thank you for joining us to discuss our first quarter fiscal 2027 results. We are pleased to report a strong start to the year with continued strength in sales execution. We beat across all guided metrics and demonstrated the constant currency growth acceleration in revenue and sales-led subscription revenue that we called out last quarter. Q1 total revenue was $478 million, growing 15%. Sales-led subscription revenue grew 18% to $399 million, and we delivered a non-GAAP operating margin of 16.2%. As we previously noted, we entered fiscal 2027 with a plan to accelerate our sales-led subscription revenue growth on a constant currency basis over the course of the year, and our Q1 results demonstrate that we are off to a good start. Customer demand was strong across all solution areas, especially in search and AI and security. We ended Q1 with more than 1,800 customers spending $100K or more in ACV. This is the highest quarter-over-quarter net additions to this $100K metric that we have ever seen. Our 21% CRPO growth and 27% RPO growth signal that customers are continuing to make multi-year commitments to our platform as long-term AI transformations are taking hold. AI is reshaping the stack that developers build upon. The focus is no longer on token maxing. It is on building agentic applications that leverage the reasoning and inferencing power of LLMs on a business's proprietary data. This requires the highest possible retrieval accuracy at the lowest possible cost. That shift plays directly to Elastic's strengths, and we have invested accordingly in critical areas. First, we have invested in a highly optimized data store and retrieval for AI. Our goal is for Elasticsearch to be the best store for all data that our customers care about, enabling text, vector, and hybrid search across structured and unstructured data, spanning text, vectors, images, audio, video, and more. We released VectorDB index mode and auto-calibration this quarter, giving developers a high-quality vector search experience out of the box with no manual tuning required. One platform with support for every data type AI demands. Second, in precisely accurate context, we continue to be one of the world's most powerful context platforms for AI. This quarter, we brought Jina's multimodal and multilingual semantic search capabilities, including first-party embedding and re-ranker models to on-premises and air-gapped environments. This extends the power of our first-party models to the world's most sensitive, regulated, and security-conscious deployments. Our Agent Builder harness continues to mature as well, enabling developers to build agents directly on top of data in Elasticsearch. Agent Builder now offers advanced agent observability, monitoring, and enhanced human-in-the-loop approval workflows, giving enterprises the control and visibility they need to deploy AI agents with confidence at scale. Our investments are translating directly into competitive wins. A Global 2000 semiconductor company selected Elasticsearch Serverless in a seven-figure new logo win to power a personalized, AI-driven knowledge search experience for its customers. Elasticsearch will serve as a context layer, transforming the company's vast product catalog into real-time grounded AI context. When a customer queries a chip specification, compatibility requirement, or part number, Agent Builder returns an accurate answer with per-user document-level security, ensuring each customer sees only what's relevant to them. In a competitive RFP against pure-play vector databases and other platform players, our hybrid semantic retrieval and natively integrated agentic capabilities were the decisive differentiator. AI is also changing the arena of observability. As organizations build and deploy more agents, it requires more scalable monitoring of the entire application stack at a lower cost. The speed and scale of AI deployments is requiring more automation for SRE teams to streamline the process of detecting, investigating, and remediating issues. We are pushing the frontier in these areas through targeted investments. This quarter, we relaunched our metrics offering. We released Columnar Mode in Elasticsearch 9.5, now in technical preview. Columnar Mode is an entirely new index mode, purpose-built for time series data. It delivers extremely efficient compression, storage, and querying of time series in a columnar data structure, pushing storage costs down 20% to approximately three bytes per metric sample, while still using the same ESQL query language. With these innovations, we are now an optimized engine for multiple types of data, including documents, vectors, logs, metrics, and more. Columnar Mode makes the Elastic Platform a highly competitive solution for metrics and infrastructure monitoring, an area where we historically have not had a major presence. Additionally, we now support native Prometheus ingestion with PromQL support, simplifying the migration from Prometheus into Elastic. No new tooling or retraining is needed. We are giving teams full visibility across metrics, logs, and traces in one unified platform, all at a very compelling price compared to incumbent competitors. We also acquired Deductive AI, a leader in the emerging space of AI SRE. Deductive has built a reinforcement learning, or RL, harness that automates the task of complex investigations. It pairs upstream data like code repositories and Elastic alerts with downstream signals from Slack, PagerDuty, and ServiceNow to dynamically construct decision trees as it learns from past and ongoing investigations. It then uses these to drive automated investigations for new incidents based on past learnings. This allows SRE teams to significantly reduce the time to investigate and remediate problems to achieve the goal of an AI-led SRE organization. By integrating Deductive's reasoning capabilities into our observability platform, we are building a true agentic SRE, one that can autonomously detect, investigate, and guide remediation across the full signal stack. This quarter, Gartner recognized Elastic as a leader for the third consecutive year in the Gartner Magic Quadrant for Observability Platforms, reflecting the strength of where we already stand. Illustrating the power of this unified platform approach, a leading global insurance company added Elastic Observability to its existing security deployment in a seven-figure expansion win. The customer had been running a fragmented environment, with application logs in Elastic and metrics and traces in another incumbent solution, preventing effective root cause analysis across tens of thousands of annual incidents, half attributable to application issues. The deciding factor was Elastic's newly released native Prometheus ingestion and PromQL support, which met their heavily metrics-driven environment where it was, and combined with our migration tooling, enabled full consolidation onto a single OpenTelemetry first platform without any costly rip and replace. Looking ahead, the ability to apply Elastic AI agents across all signal types to intelligently identify root cause was a key driver of the expansion. In a post-MITRE world, organizations are facing an increasingly challenging landscape where vulnerabilities are being discovered at an alarming rate and weaponized at machine speed. This requires cyber defenders to detect, investigate, and mitigate at speeds well beyond human capacity alone. To bridge this gap, AI-driven automation has become an absolute necessity for cyber defenders. Accordingly, we have invested in several areas to help our customers achieve their end goal of an AI-driven SOC. Attack Discovery reached a new milestone this quarter. It now investigates and validates threats autonomously, allowing SOC teams to move at machine speed. Attack Discovery turns a wall of alerts into a prioritized list of real attacks and moving security teams closer to alert zero. Alert zero is the SOC's version of inbox zero. A queue worked down to the attacks that actually matter, with agents and analysts operating together. This quarter, we were named a leader in the IDC MarketScape for worldwide SIEM and a strong performer in the Forrester Wave for extended detection and response. Forrester specifically recognized that Elastic's strategy envisions an open agentic SOC that will automate operations. Elastic XDR integrates seamlessly with our SIEM and Attack Discovery capabilities, enabling protection and remediation on affected systems to counter AI-scale threats. On endpoint protection, Elastic Security is the only vendor to achieve 14 consecutive months of 100% detection rates in AV-Comparatives independent testing. Our strength in security is also allowing us to rapidly grow our footprint in the U.S. public sector through the CISA SIEM as a service offering. This relationship continues to serve as a powerful channel across the U.S. government, opening new opportunities. A large U.S. public sector agency chose Elastic Security and Observability to begin unifying its fragmented data estate onto a single platform, replacing disparate SIEM data. Elastic's newly achieved FedRAMP High authorization unlocked the opportunity, and our ability to monitor both on-premises and multi-cloud environments from one managed deployment made us the strongest candidate. Where the agency's previous vendor had stalled on innovation, Elastic's pace of development and LLM-agnostic AI integration gave them a clear path forward for modern threat detection and response. Our efficiency and AI features were key drivers of this win. What is exciting about this customer is that we were able to migrate their very complex data platform from their incumbent solution onto Elastic in under one month, taking advantage of all of the automated migration tooling that we have built for this purpose. We see the same momentum in the private sector. A global semiconductor manufacturer chose Elastic Security Serverless as its security analytics platform to protect against insider threat and secure its intellectual property using our AI capabilities. The customer intends to move hundreds of dashboards from an incumbent solution into Elastic to leverage our natural language search and analytics capabilities. Moving away from manual workflows, the customer is adopting our agent capabilities across their full data estate. Where competitors offered AI as an add-on, Elastic's fully integrated platform gave the customer exactly what they needed, one product built for the age of AI. All of these innovations, combined with the consistent sales execution, are driving rapid growth in AI usage within our customer base. Over 37% of our 100,000-plus ACV customers are now using Elastic for AI, up from approximately 21% a year ago. That is more than 670 high-value customers now using Elastic for AI use cases, with 70 net additions quarter-over-quarter in Q1. Our ability to deliver all of this with an open platform across both cloud and self-managed deployments is proving to be an enduring advantage as AI adoption grows across AI natives, enterprises, regulated industries, and government agencies around the world. This includes our support for both proprietary models and open models like GLM from Zhipu AI, our adherence to standards like OpenTelemetry, our ability to support sovereign deployments through our self-managed offering, and our partnerships with NVIDIA and Dell around their AI factory and with Google Distributed Cloud. We entered this fiscal year with seven successive quarters of strong sales execution and continuing momentum for our platform. Our pace of growth in search and AI and security has continued. With our most recent innovations in the areas of metrics and AI SRE, we are excited about the prospects of our Observability business. As AI adoption grows across the enterprise, we expect to continue driving acceleration of our business toward our midterm revenue and profitability targets. I also want to take a moment to recognize a board transition. I want to thank Caryn Marooney, who will be stepping off our board after a long tenure. We are grateful for her partnership, and she will continue to be a friend to Elastic. I am pleased to announce that Julia Liuson has been nominated to join our board. Julia has seen Elastic grow as a leader in the areas of search, AI, Observability, and Security in her prior role as President of Developer Tools at Microsoft. She brings a unique perspective around AI and at-scale infrastructure development that will be invaluable as we continue to execute on our strategy. I want to thank our customers and partners for their trust, our shareholders for their continued partnership, and our employees for their focus and execution. With that, I will turn the call over to Navam. Thank you, Ash. On our last earnings call in May, we expressed confidence that our commitments we secured in fiscal 2026, combined with our continued sales execution, would drive revenue acceleration over the course of fiscal 2027 on a constant currency basis. While it is still early in the fiscal year, our Q1 results put us on track to achieve this goal. Our total revenue in the first quarter was $478 million. We grew approximately 15% as reported and on a constant currency basis. On a constant currency basis, Q1 growth accelerated quarter-over-quarter up from 14% in Q4. Sales with subscription revenue in the first quarter was $399 million. We grew 18% as reported and 17% on a constant currency basis. Similar to total revenue, sales-led subscription revenue accelerated quarter-over-quarter in constant currency up from 16% in Q4. Our CRPO in the first quarter was $1.2 billion, representing 21% growth as reported and 20% on a constant currency basis. Our constant currency CRPO growth sustained 20% growth for the second consecutive quarter. Our RPO for the first quarter was $1.9 billion, representing 27% growth, both as reported and on a constant currency basis. As Ash mentioned, the continued strength in RPO reflects customers deepening their long-term commitments to Elastic as a core part of their AI infrastructure. Our Q1 revenue acceleration on a constant currency basis, both for total and for sales-led subscription revenue, as well as our second straight quarter of 20% constant currency CRPO growth, provides validation for our acceleration trajectory. Three core dynamics are powering our fiscal 2027 sales-led subscription revenue growth. First, our strategic investments in sales capacity over the past year are driving the pipeline improvements we expected. Building on seven quarters of go-to-market improvement, we continue to see year-over-year gains in both ramp sales headcount and productivity this quarter. Additionally, the strength in our second quarter pipeline and build-up of outquarter pipeline reinforce our confidence in securing new and expanded commitments, as well as achieving our planned renewals. Second, as we discussed last quarter, a portion of our fiscal 2027 revenue is made up of commitments from fiscal 2026, now being consumed and converted into revenue. We are pleased with the healthy consumption activity we saw this quarter. The net expansion rate, or NER, remains strong, though it moved from 112%- 111% this quarter. As a reminder, our NER is a four-quarter trailing metric impacted by historical growth. The NER we reported in Q1 reflects the lower constant currency growth rate in the trailing four quarters as compared to the four quarters preceding it. We expect NER to improve within four quarters as constant currency revenue acceleration builds through fiscal 2027. Third, we saw continued improvements in our new and expansion commitments, as seen in our greater than 100K customer count, a segment now contributing 90% of sales-led subscription revenue, up from 87% a year ago. This quarter, we added more than 80 net new customers to this tier, our largest increase to date. This reflects the effectiveness of our sales team in both winning new logos and expanding within our existing base. Now turning to Q1 margins and profitability, I will discuss all measures on a non-GAAP basis. We delivered subscription gross margins of 81%, total gross margins of 77%, and an operating margin of 16.2%, exceeding our guidance from last quarter. The improvement in margins reflect the operating leverage in our model as revenue scales. We achieved an adjusted free cash flow margin of 30%, despite one-time charges related to organizational changes we announced in June. These amounted to $13 million of cash paid for restructuring and other charges. As a reminder, adjusted free cash flow fluctuates quarter to quarter due to booking seasonality, and we manage free cash flow on a full-year basis. During the first quarter, we returned approximately $40 million to shareholders, representing purchases of approximately 800,000 shares. Since the $500 million share repurchase program launched in October 2025, we used $380 million and repurchased 5.2 million shares cumulatively as of the end of last quarter. Now turning to our outlook for the second quarter and for the fiscal 2027. Building from the momentum we experienced in Q1, we are raising our previous guidance for the full year. For the second quarter of fiscal 2027, we expect total revenue in the range of $486 million-$487 million, representing 14.9% growth at the midpoint or 15% constant currency growth at the midpoint. We expect sales-led subscription revenue in the range of $407.5 million-$408.5 million, representing 16.9% growth at the midpoint or 17.1% in constant currency growth at the midpoint. We expect non-GAAP operating margin for the second quarter to be approximately 19%. We expect non-GAAP diluted earnings per share in the range of $0.80-$0.82, using between 108 million and 109 million diluted weighted average ordinary shares outstanding. For fiscal 2027, given our strong Q1 results, we are raising our outlook for the year. We expect total revenue in the range of $1.998 billion-$2.010 billion, representing approximately 15.2% growth at the midpoint or 15.3% constant currency growth at the midpoint. We expect sales-led subscription revenue in the range of $1.682 billion-$1.694 billion, representing 17.4% growth at the midpoint or 17.5% in constant currency growth at the midpoint. We expect non-GAAP operating margin to be approximately 19.4%. We expect non-GAAP diluted earnings per share in the range of $3.29-$3.37, using between 108.5 million and 109.5 million diluted weighted average ordinary shares outstanding. We continue to expect our fiscal 2027 adjusted free cash flow margin to be 21.5%. We are growing revenue efficiently while maintaining disciplined investments and are making progress towards rule 40. Before I close, a few more financial items worth highlighting related to this year. We incurred approximately $20 million of restructuring-related charges during the first quarter, and we expect to incur an additional $2 million-$5 million of restructuring charges for the remainder of the fiscal year. We expect our GAAP operating margin to be positive in the second quarter and for the full year. We also expect to maintain GAAP operating margin profitability going forward. As we said last quarter, we expect total revenue and sales-led subscription revenue growth to accelerate in the second half, with Q4 having the highest year-over-year growth for the year. To summarize, we are executing well across our fiscal year priorities and are firmly on track to meet our medium-term financial targets of both accelerating our sales-led subscription revenue growth to 20%+, and improving our rule of 40 as measured as the sum of revenue growth and adjusted free cash flow. The sustained progress we see in CRPO, sales productivity, pipeline, and operating leverage reinforce our confidence in our revenue growth and margin expansion plans. Elastic continues to be the essential platform for enterprises looking to derive value from their data, and we look forward to the opportunities ahead. Thank you for your continued support and for joining us today. With that, I'll open it up for Q&A. We will now begin the question and answer session. To ask a question, you may press star then one on your telephone keypad. If you are using a speakerphone, please pick up your handset before pressing the keys. To withdraw your question, please press star then two. Our first question today comes from Matt Hedberg with RBC Capital Markets. Please go ahead. Great. Thanks for taking my questions, guys. First of all, congrats on the quarter. The acceleration, especially after a Q4, was impressive. Ash, there's a lot of things that stood out to me, the strength in 100K customers. I think you said the largest sequential add you've ever seen was impressive. I guess you talked about a lot of things on the call about execution and product traction and just better sales capacity, but I'm wondering if you can put a finer point on the success there. Why now? Just kind of the sustainability of that large customer growth would be great. Matt, thank you very much for the question. Like you said, it was a great quarter in terms of the net adds. We added 80 customers to that cohort, the highest ever number of additions that we've had. Fundamentally, the way I think about it is that our new and expand motion, especially in our enterprise and mid-market high propensity customers, is working really well. If you remember, about two years ago, a little over two years ago, we made a change to the way we did segmentation within the organization, within the sales organization. Since then, you have seen us continue to improve in this area. What you're seeing is customers are making bigger commitments, customers are making longer-term commitments, and that's resulting in this cohort really growing very nicely. By the way, this 100K cohort now represents 90% of our sales-led subscription revenue. It just gives you a sense both of how important this cohort is, but also how well they are doing. The thing that excites me the most is the AI penetration in this cohort. So 37% of this 100K cohort is now using our AI features. That number was about 21% in the past. Like we explained even at our financial analyst day, the more this high-value customer cohort uses our AI capabilities, the more they use more and more solutions within our platform, that really becomes the enduring growth driver for us. So very excited about it, and it just shows that the go-to-market motion is working and the platform strength and differentiation is holding very well. Well, if I could, as a follow-up, the 37% of those customers using AI, it was another thing that stood out to me. Is there any way to think about what that means from an NRR perspective? I'd have to imagine it's obviously additive and maybe it's part of the NRR re-acceleration. But just any way to think about what that means from a customer ACV or NRR perspective? That question. The NRR is obviously a strong metric across the board for all our 100K customers. But when you think about the cohort of customers that are using AI, the dynamics that we talked about during the financial analyst day still stand, which is they have a higher growth propensity compared to customers not using AI. So that dynamic exists today among that AI cohort group, the same way it existed when we talked about in the financial analyst day. Great. Thanks. Thanks, Matt. Next question, please. The next question comes from Tyler Radke with Citi. Please go ahead. Tyler? Hey, can you guys hear me okay? We can now. Sorry about that. Was on mute there. Can you just talk a little bit, obviously really strong Cloud performance, and I know you alluded to the strength in the Cloud bookings last quarter, but any one-off dynamics we should be mindful of? Can you just comment on sort of the bookings mix this quarter, how that Cloud sort of looked relative to historicals and just any color on how we should be thinking about the growth of Cloud from here? Yeah. Thanks, Tyler. It's Navam here. Look, we're very pleased with the way Cloud has been performing in the quarter, both in terms of the commitment volume and also, more importantly, the consumption against the annual commitments we have, the aggregate annual commitments we have. As a reminder, Cloud's not a guided metric and there's always going to be quarter-over-quarter variability because it's consumption. But our annual Cloud growth improved to 27% this quarter, up from 26% last quarter. On the monthly Cloud side, that number, we expected it to remain flat, and it remained roughly flat for the quarter. So the dynamics are roughly the same in terms of the growth on the sales-led Cloud side and the SMB smaller customers remaining flat. At the end of the day, though, we win because we have flexibility in our deployment model, right? And we meet the customers where they are and where they want to deploy our software. And we are one of the very few players that can actually do that. And that's the reason we continue to focus on sales-led subscription revenue. In terms of bookings dynamics, we expect to, like I said, meet customers where they are. There isn't much to call out this quarter in terms of one-offs. We talked about the mix in Q4 being a good cloud quarter. Q1 remained a solid quarter with no unusual activity one way or the other. And by the way, Tyler, just to put a finer point on what Navam said, the fact that we can deliver all the capabilities that we provide through the platform, whether it's for AI, whether it's for security, whether it's for Observability, in environments ranging from commercial cloud, to people running it in their own data centers, to air-gapped environments. We mentioned last quarter that Google Distributed Cloud has OEM'd our capability as well. So that flexibility, that range, is a significant enduring moat. Because if you think about the markets that we play in, there are very few vendors that have that ability to deliver across all of those form factors, and that is a big advantage for us, and that's the reason why, as Navam said, sales-led subscription revenue is a very important metric. And by the way, cloud, self-managed, all of those are things that we look at, and we are very happy about the performance overall. Great. Ash, maybe just to get a follow-up for you. Obviously, some pretty remarkable events going on in security as it relates to some of the new attack vectors and agents going rogue. Can you just talk to us about the Elastic Security business? How do you see it participating in some of these new agentic security fronts? Yeah. Our security business is something that we are very excited about. Even in my prepared remarks, Tyler, I talked about several customers that are using us in security. I talked about the semiconductor company. I talked about the very large government agency. We've talked to you in the past about CISA SIEM as a service. I just mentioned Google Distributed Cloud. All of these are already driving our SIEM business and our XDR business. What's great about this is we are able to help our customers because it's never been harder to be a CISO. Vulnerabilities are being discovered faster, threats are being activated faster. So working at human speed is just not sufficient. You have to figure out how to use AI on the defender side to be able to detect, investigate, and remediate at machine speed. You know how early we invested in the AI-led capabilities like Attack Discovery and so on. All of that, the maturity, the continuous innovation that we are driving there, we are already seeing all of this turn into strong commitments, and you're seeing now the consumption against those commitments. So I expect the momentum to continue for us in security. Great. Thanks. Tyler, next question, please. The next question is from Miller Jump with Truist Securities. Please go ahead. Hey, great. Thank you for taking my question, and congrats on the strong results here. I am wondering if you can give any more color on how you are seeing the distribution of customer AI deployments developing specifically across cloud, on-prem, and hybrid, and if there is any difference versus your other use cases. Yeah. What we are seeing is that there is still the majority of customer deployments tend to be first and foremost in cloud. That is where they typically start, because that is the fastest way for customers to get started. But enterprise customers and government agencies, and when I say enterprise customers, I am specifically referring to customers in regulated industries, whether it is banking, whether it is telco, especially in international markets for us outside of the Americas. What we are seeing there is a greater desire to not just have data sovereignty, but also to have operational sovereignty. In those environments, they want solutions where they can run these capabilities within their own enclaves, within their own control. Again, that is where we have such a great strength, because there are not too many companies that are able to provide that kind of functionality. In the past, our Jina models, you had availability of the commercial Jina models through our inference service, which was cloud only. But there was no way, if you are an air-gapped customer or a customer running things within your own enclave, to take advantage of the Jina models. We did not have a pricing model in place for the commercial capabilities there. That is what we launched, and there is a lot of interest. We launched it because we are seeing a lot of interest. Going forward, what I would expect is AI deployments are going to be based on factors like the criticality of the data, the sensitivity of the data, the kind of customer, and their geolocation. Those will be bigger factors, but you are going to see AI adoption both in cloud and in self-managed. Really exciting. If I could just squeeze in a follow-up for Navam. You all highlighted the strength in the CISA deal. But just given that we're coming up on the anniversary, I'm wondering if you can give any more color on how the Fed vertical is being treated in the Q2 guide, and if there's any headwinds or tailwinds we should consider this year. Nothing specific at this point in terms of guidance for the Fed vertical, Miller. The global public sector remains an important sector for us. When we think about our guidance, we obviously look at a prudent risk-adjusted view as to the forward numbers. Very pleased with how the CISA contract is performing and the continued activity there. We expect that to continue to gain momentum as more agencies come on board. But nothing specific to call out in terms of a big tailwind coming in or a big headwind coming in from the federal segment. Awesome. Thank you. Thanks, Miller. Next question, please. The next question is from Brian Essex with JP Morgan. Please go ahead. Hey, good afternoon. Thank you for taking the question and congrats from me as well on the results. It is great to see that acceleration. Maybe Ash for me, I would love to get your view on how you see your customers deploying AI and coding around AI, specifically around leveraging your platform to build their own harness in context windows to get more control around the ability to protect that context, IP, and proprietary data, as opposed to using OEM harnesses and coding platforms, and how you are positioned for, or your view on how that portion of the market is going to evolve over the next few years. Yeah, thanks for the question. The first thing to appreciate is, at the end of the day, when you are building any kind of agentic solution, the most important element in that is going to always be the large language model, the model that does reasoning, that does inferencing, so on and so forth. But that model, unless what the agent that you are trying to build only depends on external data, only depends on publicly available information, is going to need to somehow be coupled with your proprietary information. Now, if you think about any enterprise, you think about any large agency, the biggest challenge is now you are talking about many petabytes, if not exabytes of information that is constantly being created, information that is constantly changing. This really ends up being a situation where you have to bring the model to the data. The data is just too much to take to the model. More importantly, that data is your secret sauce, so you never want to have it completely exit your organization anyways. That is really why, as you think about what people are building with harnesses and so on, the most important element in that is sort of the data retrieval or the context layer. When you are trying to get that context for your LLM, for your agent, you have to worry about accuracy, you have to worry about speed, and you have to worry about cost. What that means is you really want to try and precompute as much of that context ahead of time as possible, so your model is not just constantly trying to sift through all of the data every single time, which is a very expensive, very inefficient, very slow approach. That's what we do. That's where we fit in. That's the reason why customers turn to us, because we are able to make their agents perform better, we are able to make their agents more secure in how they operate, we are able to provide just the right context to their agents, and we are able to reduce cost and give them that balance of both using proprietary models where it makes sense, using open models where that's the best approach. That flexibility, that deployment choice, all of this is how people are using us today, and that's why we believe that this is something that's an enduring motion for us. It's an enduring area for us to grow on. Got it. That's super helpful color. Maybe just for a follow-up, security as a percentage of total revenue and in a post-Mythos world, how do we think about contribution from that business relative to the rest of the Elastic Platform? Thank you. As a percentage of revenue, we don't disclose that, Brian, but in terms of growth- Okay security remains a very strong growth vector for us, and we've highlighted this in the past earnings call as well as to the contracts and the customers that we have on the security side. So very pleased with how that's performing, and it remains to be a high-performing, high-growth segment for us. Even this quarter, if I may just add to what Navam said, security grew incredibly well. The order roughly was security, AI, search AI, and then observability. With observability, with what we are doing around metrics, the Deductive acquisition, like that is the third pillar of the stool, if you will. That is what gives us a lot of optimism in the future. So really, we feel really good about the way our platform story is evolving here. All right. Thanks, Brian. Next question, please. Great. Thank you. The next question is from Rob Owens with Piper Sandler. Please go ahead. Thanks for the question, Alex, and good afternoon, everybody. In your prepared remarks early on, you talked about success in the quarter. You talked about search and AI and security, and I know you've got new capabilities in Observability. Ash, you just mentioned some of them, but maybe you can drill down relative to the metrics opportunities, some of the new pricing dynamics that you offer, and just what customer feedback or acceptance has been at this point. Yeah, thanks for the question. Rob, the way we have built our Observability business over the years is starting with logs. As you know, log analytics was where we started because the messier the logs, the more capable our solution has been in giving you the ability to do full-text search through those logs, to do analytics on those logs. So our strength in log analytics continues. It's been a huge area for us, and over the years, we've continually made our platform more efficient for log analytics, which is another reason why we continue to do well in that area. Sort of expanding from there has been an area where as we've looked at the market, what we realized was metrics because of AI and what's been going on in terms of people building these agents, that's an area where we didn't have that same kind of strength. We didn't have that same kind of performance. So about a year and a half ago or so, we started working on a completely novel backend to Elasticsearch that allowed us to have not just the regular document store model that we had in Elasticsearch, but also a Columnar Mode backend, all accessible through the same API. Because, again, we want to make it easy for people to adopt this columnar backend. This columnar backend has been really tuned for basically all kinds of time series data, so metrics, and even simple logs. This columnar approach makes it possible for us to store the data in a much more efficient way. So the storage efficiency is massively higher. The ingest performance is better. The query performance is better. So we get a ton of benefits, and it's going to show up most in metrics. In the past, it used to take us double-digit bytes to store metrics. We are now able to store a single metric in around 3 bytes, which is a huge difference. Now we are incredibly competitive in the market. This is going to allow us to really take on this area head-on. We are early, I have to say, but the early feedback that we've gotten from customers, because we are going to our existing log analytics customers and upselling there, has been very good. We are excited about the feedback that we are getting. The way I see it is, if we do this right over the next year, multiple years, this is going to be a pretty significant and meaningful area of growth for us. Great. Speaking of early, you mentioned a number of autonomous innovations this quarter across both security and Observability. Curious, just early feedback from customers. Obviously, the security landscape is changing rapidly. For those on the bleeding edge, how are they consuming? What does overall consumption look like? What's that relative state of change for those that are moving to some of these autonomous capabilities? Thanks. Our AI SOC capabilities on the security end have been a big reason for our success in security. You've been seeing us do very well in security for the last many quarters, and I attribute a lot of that to the investments that we made and the differentiation that we have in our agentic capabilities when it comes to security. The biggest differentiation that I still hear from our customers is not only do we have a very complete set of capabilities out of the box, but unlike others who have a black box approach to AI, we have more of an approach where we allow you to see what's under the covers. You can see the skills, you can see the tools inside the harness, inside the security harness that we built. You can complement it, you can enhance it, you can do more with it. That is a big differentiator, because at the end of the day, we believe that models are going to keep getting better and for different tasks. Some tasks you're going to prefer to use Claude, for others, you're going to prefer to use Gemini. For something else, you might use an open source model. Also, skills will continue to evolve, harnesses will continue to get better, and we believe that giving that openness and choice to our customers will be an enduring differentiator, and that's what we are seeing so far. Thanks, Rob. Just as a reminder about our metrics webinar on September 22, that information is going to be posted on the ir.elastic.co website. With that, let's go to the next question. The next question is from Raimo Lenschow with Barclays. Please go ahead. Perfect. Thank you. Congrats from me as well. Great quarter. A couple of weeks ago, you launched a Kubernetes capability on the Observability side. Can you speak to the importance of that? That seems to be closing a really important gap in the offering. Maybe just to speak to what's possible now. Thank you. Yeah. A lot of it has to do, Raimo, with our focus on having a great end-to-end experience. The areas that we want to make sure customers adopt us increasingly for is using us for metrics, using us for infrastructure monitoring. As you know, a lot of agents are being deployed on Kubernetes environments and getting that right with a great end-to-end experience with dashboards that light up out of the box, with native support, not just for OpenTelemetry-based ingestion and analytics, but also support for Prometheus data and PromQL. These are areas where we've invested a lot. Even in the prepared remarks, the customer that I talked about that chose us for metrics, that customer moved to us because we made it so easy for them to bring their Prometheus data directly into Elastic without having to transform things, without having to change things. That's a big differentiator. You're absolutely right to look at that and see that that is a key element. It is one of many investments that we've been making on the Observability side, that's what is quite. We find that to be quite exciting for the days ahead. Perfect. Yeah. No, thank you. Yeah, same view here. Another one for you. You only had your Q1, but you raised the full year by more than the beat. Q1, nowadays in software, everyone is very conservative, et cetera. What gave you the confidence there? What are you seeing in terms of pipeline, et cetera? Thank you. Yeah. Thanks, Raimo. I don't think the guidance philosophy has changed much compared to what we've done in the past. We've always taken a prudent and risk-adjusted view to guidance. Like you said, it is only Q1, but it was a good start to fiscal 2027, and we got some strong data points from that quarter. Our CRPO, obviously, which was a good number, and the RPO number, as well as the 100K adds. Apart from that, there were three specific drivers that we saw internally as well. First is the strong pipeline build, both for the second quarter and the full year. The outquarter pipeline build is looking good. Second is the consumption against the CRPO committed CRPO number performed well. Then third, we expected a certain productivity and capacity increase given the hiring that we did, and we're seeing that, and that's allowing us to have the confidence on the go-get number that we need to do for the net new revenue side for the rest of the year. That's the reason we guided the way we did, and we're encouraged about the revenue trajectory for the year. The philosophy hasn't changed, but we feel good about what we need to go achieve for the rest of the year. Thanks, Raimo. Next question, please. Next question is from Howard Ma with Guggenheim. Please go ahead. Great. Thanks for taking the question, and I want to add my congratulations, too, on a strong quarter. My question is the acceleration that you're seeing, would you say that that's directly attributable to higher multi-product adoption driven by the realization that Elastic is an attractive solution for both context engineering and managing the agentic-driven proliferation in telemetry data as opposed to point solutions? Does your guidance factor in material acceleration in cross-sell among various use cases? Yeah, maybe let me touch upon that and then I'll let Navam talk about all things related to guidance. But if you think about our motion, it's always, Howard, been very similar, right? We have a platform that allows customers to do multiple things. What we focus on is making sure that our platform is incredibly good in each of those areas. So each of our solutions are focuses on making sure that those solutions are able to be differentiated and stand on their own and win on their own. That becomes the tip of the spear for us. It's our land and then expand strategy. Because once we land with one solution, then the goal becomes how do we get the other solution in there and the third solution in there. And obviously, like we had talked even at our last analyst day, the customers that grow the fastest are the ones that adopt us for all three solutions. So that land and expand motion has continued, and it is not that necessarily that has inflected in any way, but what you are seeing here is just the right kind of progression. This is a motion that we have been driving. Probably the biggest thing that has happened is as our focus on our enterprise selling motion, the segmentation change that we did 2 years ago, as that has matured, we are seeing the benefits of that play out very nicely. So our land and expand is working in all three solution areas. We are seeing the right kind of movement. Look, it comes down to making sure that you are positioning your platform, your product in the right way. Then our sales teams know how to position the multiple product strategy within that platform, and that is why we feel so good about what this is going to mean for the future. In terms of the guidance, Howard, there is nothing different implied in how our land expand motion works. Obviously, a lot of our revenue comes from expand more than land. Land is the entry point, and then expansion is where the dollars come in over time. That dynamic comes from both expansion of the existing product that you bought and also cross-sell. So there is not anything in the guidance that we have taken into account a different behavior from our customers from what we currently see. Okay. Thanks, Howard. Next question, please. In the interest of time, please limit yourselves to one question. The next question is from Radi Sultan with UBS. Please go ahead. Awesome. Yeah. Thanks for taking my question. Ash, in your prepared remarks, you called out a SIEM migration, which I believe you said got done in under a month with some of your automated migration tooling. I just wanted to ask, how much of a benefit are you seeing to cloud consumption from AI accelerating migrations on the SIEM side, but also maybe just more broadly? Yeah. The strength in consumption that we saw this quarter was broad-based. It was not related to any one customer. But what I talked about there, which is really important to understand is, at the end of the day, SIEM has never been greenfield, right? SIEM as a space has been around for a long time, and our motion has been to displace the incumbents who are not innovating at the same rate. What's really changing there, to be honest, is the environment. People are really worried about what it means to protect your environment, protect your agencies, and so on, in a post-Mythos world. And it's not just Mythos. There are so many very capable models out there, not just commercial models, but open source models that give you the ability to really discover vulnerabilities and then act upon them. You have to assume that people who are trying to do harm now have the ability to access these models, so defenders are having to move faster and so on. So that is driving the momentum for our business and the ability with our automated tooling to migrate these customers from their incumbent solution to our product, our platform. We have gotten really good at it. This was a very significant sized agency, and we were able to move their massive real estate over in under one month. And that is just a- The thing that gives our field a lot of confidence, it is what gives our customers a lot of confidence, because as they see these things happening over and over again, it gives them confidence that they can safely move to Elastic, and that we will be able to make them successful quickly. All right. Thank you. Next question, please. The next question is from Shrenik Kothari with Robert W. Baird. Please go ahead. Mr. Kothari, your line is open on our end. Perhaps you have it muted on yours. All right. I think we need to go to the next question then. The next question is from Matt Cikos with Needham. Please go ahead. Hey, guys. This is Matt Calitri on for Mike Cikos over at Needham. Thank you for taking our questions. You gave some great color on that 100K cohort and some of the AI adoption, which we appreciate. Are there any other clear underlying expansion trends you can share regarding older cohorts versus newer ones or smaller customers versus larger ones? Is it more so just expansion across the board and you are waiting for that trailing 12 months net expansion number to catch up, as you mentioned on the prepared remarks? Yeah. Thanks, Matt. The trailing 12-month number on the NRR. The NRR side is impacted by the trailing 12-month constant currency growth. That is a separate factor. As constant currency growth improves alongside guidance that we have provided, it is going to take a lagged effect for the NRR to catch up. That is the comment on the NRR side that I was making. On the cohort behavior, the cohort behavior that we talk about is basically a durable land expand motion. We get our customers in, and there is a long period of durable expansion that we expect from every one of those cohorts, and that is continuing. We also expect to see, and we see, the AI cohort show a differential in our growth, meaning the customers who are using our AI features are effectively expanding at a slightly higher rate than the ones that are not. Those are the two dynamics that we see in our expansion rates, and those trends are continuing. As I mentioned, NRR, which is trailing, ticks up alongside the revenue growth rate that we expect to post for the year. All right. Thanks, Matt. Next question, please. The next question is from Sanjit Singh with Morgan Stanley. Please go ahead. Yeah, thank you for taking the questions. Ash, I see a lot of the passion on the SIEM side, and obviously throughout the other core parts of the business as well. I wanted to come back to the AI search part of the business. We have a lot of data platform players trying to solve that context semantic problem. I think Palantir's done it in a proprietary way. From the Elastic perspective, in terms of getting that agent performance and building that map for that agent, why is Elastic able to do that better than some of the other data platform peers that are trying to solve that similar problem? The simple answer, Sanjit, is because we've always been optimized for dealing with messy data, for dealing with unstructured data. Most of the data platforms that you're talking about, that you might be thinking about, were all designed to work with structured information. Fundamentally, although they might have had a sort of NoSQL view of the world, it was still sort of designed with strict schemas structure in mind. Elastic has always been different in that sense. If you think about Elastic, we started as a document store with an inverted index that allows you to put any and all kind of information in it, which is why we were always used for search, which is why we then moved into log analytics, because all of these things end up being very unstructured. The schema keeps evolving. If you think about the kind of information that is being used primarily, a lot of it in AI is this kind of unstructured data. Our strength in terms of being able to bring in this data, being able to then analyze it, search across it, the capabilities that we've built, not just with vector search, but also around hybrid search, the harnesses that we've built on top of it, all of this, the Jina models, our ability to do re-ranking and so on, we are way ahead of the competition, especially when you look at things from this unstructured lens. Frankly, Sanjit, we feel that we are still very early in this overall phase of AI adoption. Most organizations are only now starting to really deploy things in a meaningful way. As that grows, as we have more penetration within our customer base, I think that is going to be what really helps us continue this momentum for a very long time. All right. Thanks, Sanjit. Appreciate it. Next question, please. The next question is from Ryan MacWilliams with Wells Fargo. Please go ahead. Hey, thanks for taking the question. One for Navam. How should we think about the gross margins in the quarter? It looks like they were just slightly lower versus the previous quarter. Perhaps some impact from the mix shift from cloud here, but anything else worth calling out? How to think about gross margins for the rest of the year. Thanks. Yeah. Look, we're very pleased with how our subscription gross margins are performing. It's remained above 80%. There's nothing specific in terms of a trend that emerged this quarter. But over the longer term, what we expect is that these gross margins are expected to improve as we see benefits from things like serverless as it gets to scale. So there's going to be fluctuations quarter-over-quarter, but nothing specific this quarter from a trend perspective on margins. Appreciate the color. Thank you. This concludes our question and answer session. I would like to turn the conference back over to Ash Kulkarni for any closing remarks. Thank you very much for joining our call today. We are pleased to report a strong start to the year. We are extremely proud of our results and very excited about the opportunity ahead. Lastly, please join us on September 22nd for our public webinar on metrics. Have a great day. The conference is now concluded. Thank you for attending today's presentation. You may now disconnect.