Elastic N.V. 2027 Q1 Earnings Call

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.