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Elastic Q1 earnings call highlights. Elastic (NYSE:ESTC) reported first-quarter fiscal 2027 revenue of $478 million, up 15% from a year earlier, as the company cited continued sales execution and demand across its search and AI, security and observability offerings. Sales-led subscription revenue rose 18% to $399 million, while non-GAAP operating margin reached 16.2%. Chief Executive Officer Ash Kulkarni said the company exceeded all of its guided metrics and began the fiscal year with accelerating constant-currency growth in both total revenue and sales-led subscription revenue. Discover more Weapon development trends Stocks & Bonds Nano Nuclear Energy "Customer demand was strong across all solution areas, especially in search and AI and security," Kulkarni said. Large-Customer growth and contracted commitments. Elastic ended the quarter with more than 1,800 customers with annual contract value of at least $100,000. The company added more than 80 net new customers to that cohort during the quarter, its largest increase to date. Customers in the group accounted for 90% of sales-led subscription revenue, compared with 87% a year earlier. Chief Financial Officer Navam Welihinda said the growth reflected improvements in sales capacity, productivity and pipeline generation, as well as ongoing consumption of commitments secured in fiscal 2026. Current remaining performance obligations, or CRPO, totaled $1.2 billion, growing 21% as reported and 20% on a constant-currency basis. Total RPO was $1.9 billion, up 27%. Kulkarni said the results indicated that customers were increasingly making multiyear commitments to Elastic's platform as they pursue AI-related transformations. Elastic's net expansion rate was 111%, compared with 112% in the prior quarter. Welihinda said the metric is calculated on a trailing four-quarter basis and should improve within four quarters as the company's constant-currency revenue growth accelerates through fiscal 2027. AI, security and observability initiatives. Kulkarni said Elastic is positioning Elasticsearch as a data store and retrieval layer for AI applications that require text, vector and hybrid search across structured and unstructured data. During the quarter, the company released VectorDB index mode and auto-calibration capabilities intended to provide vector-search performance without manual tuning. The company also extended Jina's multimodal and multilingual semantic-search capabilities, including embedding and re-ranker models, to on-premises and air-gapped deployments. Elastic said its Agent Builder product added agent observability, monitoring and human-in-the-loop approval workflows. More than 37% of Elastic's customers with ACV above $100,000 were using its AI features at the end of the quarter, up from about 21% a year earlier. The company said that represented more than 670 customers, including 70 net additions during the first quarter. Welihinda said customers using AI capabilities have a higher growth propensity than customers that do not use those features. In observability, Elastic relaunched its metrics offering and introduced Columnar Mode in Elasticsearch 9.5 as a technical preview. Kulkarni said the index mode is designed for time-series data and can reduce storage costs by 20% to about three bytes per metric sample. The company also added native Prometheus ingestion and PromQL support. Elastic acquired Deductive AI, which it described as a provider of AI site reliability engineering technology. Kulkarni said Deductive's reinforcement-learning harness can automate complex investigations by using information from code repositories, Elastic alerts, Slack, PagerDuty and ServiceNow to build decision trees based on previous and ongoing investigations. On the security side, Elastic said its Attack Discovery offering now autonomously investigates and validates threats. Kulkarni said the company is targeting an "AI-driven SOC," or security operations center, in response to a faster-moving cyberthreat environment. Elastic was named a leader in IDC's MarketScape for worldwide SIEM and a strong performer in Forrester's Wave for extended detection and response, according to the company. Profitability, capital returns and outlook. On a non-GAAP basis, Elastic reported subscription gross margin of 81%, total gross margin of 77% and adjusted free-cash-flow margin of 30%. The free-cash-flow result included $13 million in cash paid for restructuring and other charges related to organizational changes announced in June. The company repurchased approximately 800,000 shares for about $40 million during the quarter. Since launching its $500 million repurchase program in October 2025, Elastic has spent $380 million to repurchase 5.2 million shares as of the end of the first quarter. Elastic raised its fiscal 2027 outlook following the quarter. For the second quarter, it expects: * Total revenue of $486 million to $487 million, representing about 15% growth at the midpoint. * Sales-led subscription revenue of $407.5 million to $408.5 million, representing about 16.9% growth at the midpoint. * Non-GAAP operating margin of approximately 19%. * Non-GAAP diluted earnings per share of $0.80 to $0.82. For fiscal 2027, Elastic forecast total revenue of $1.998 billion to $2.010 billion and sales-led subscription revenue of $1.682 billion to $1.694 billion. The company expects non-GAAP operating margin of about 19.4%, adjusted free-cash-flow margin of 21.5% and non-GAAP diluted earnings per share of $3.29 to $3.37. Welihinda said Elastic expects growth in total revenue and sales-led subscription revenue to accelerate during the second half of the fiscal year, with the fourth quarter producing the highest year-over-year growth rate. The company also expects positive GAAP operating margin in the second quarter and for the full fiscal year. Kulkarni also announced that Caryn Marooney will leave Elastic's board after a long tenure and that Julia Liuson, formerly president of Developer Tools at Microsoft, has been nominated to join the board. About Elastic (NYSE:ESTC). Elastic N.V. operates as a search and analytics company, offering a suite of open source and subscription-based solutions for search, observability and security use cases. Its flagship product, Elasticsearch, enables fast and scalable full-text search and analytics across large volumes of structured and unstructured data. Complementary tools such as Kibana provide visualization capabilities, while Beats and Logstash serve as lightweight data shippers and data processing pipelines, respectively. The company was founded in 2012 by Shay Banon, who serves as chief technology officer, and Steven Schuurman.

After posting a solid earnings beat, Elastic's stock bounced higher in extended trading. Shares of the enterprise search software company Elastic N.V. soared more than 19% in extended trading today after the company delivered fiscal first-quarter results that easily beat Wall Street's targets. The company reported earnings before certain costs such as stock compensation of 70 cents per share, breezing past the analyst consensus estimate of 58 cents. Revenue for the quarter rose 15% from a year earlier, to $478 million, topping the Street's $470 million forecast. It was a strong showing by Elastic, and it helped the company to improve its bottom line. Although it still posted a net loss of $16.7 million for the quarter, that was a big improvement on the $24.6 million loss it reported in the same quarter a year ago. Elastic might not be a household name, but it's well-known in the enterprise. It's the company behind the open-source search engine called Elasticsearch, which is used by thousands of midsized and larger businesses all over the world. Elastic makes the platform free to download, monetizing it by selling a special, cloud-hosted version with premium features. It also has a growing business selling application observability and threat detection tools. In recent months, Elastic has tried to position Elasticsearch as a useful platform for feeding massive amounts of real-time data into large language models to give them the business context they need to make decisions. In a statement, Elastic Chief Executive Ash Kulkarni (pictured) said this strategy has really begun to pay off for the company. "Elastic delivered a strong start to fiscal 2027, beating our guidance across all key metrics," he added. "AI is reshaping the enterprise technology stack, and organizations are making deliberate choices about where to build and how to observe and secure their applications and data." Elastic had plenty of other encouraging figures that reflect the healthy state of its business. It said current remaining performance obligations, which are used as a measure of future revenue, rose by 21% to $1.153 billion at the end of the quarter. Meanwhile, the number of customers now spending at least $100,000 on its tools each year rose to more than 1,800, up from 1,550 a year earlier. During the quarter, Elastic bought a startup called Deductive AI Inc., which had developed an AI-enabled investigation platform that engineering teams can use to identify and resolve production issues faster. The company, which paid a reported $85 million, plans to integrate those capabilities to the Elastic Observability platform. Moving onto guidance, Elastic said it anticipates second quarter revenue of between $486 million and $487 million. That compares with the Street's target of $483 million. For the full year, Elastic is projecting sales of between $1.998 billion and $2.010 billion. That's better than the Street's guidance too, with analysts predicting annual sales of just $1.99 billion. Some investors appear to have anticipated Elastic might have a good quarter. The company's stock had gained more than 5% during the regular trading session, prior to today's results and the after-hours jump. Following those gains, Elastic's shares are now up 11% in the year to date. Photo: SiliconANGLE. A message from John Furrier, co-founder of SiliconANGLE: Support its mission to keep content open and free by engaging with theCUBE community. Join theCUBE's Alumni Trust Network, where technology leaders connect, share intelligence and create opportunities. * 15M+ viewers of theCUBE videos, powering conversations across AI, cloud, cybersecurity and more * 11.4k+ theCUBE alumni - Connect with more than 11,400 tech and business leaders shaping the future through a unique trusted-based network Are you an AWS customer? Support SiliconANGLE financially by buying your AWS services from its Marketplace portal page and links: https://siliconangle.com/aws-marketplace/. About SiliconANGLE Media. SiliconANGLE Media is a recognized leader in digital media innovation, uniting breakthrough technology, strategic insights and real-time audience engagement. As the parent company of SiliconANGLE, theCUBE Network, theCUBE Research, CUBE365, theCUBE AI and theCUBE SuperStudios - with flagship locations in Silicon Valley and the New York Stock Exchange - SiliconANGLE Media operates at the intersection of media, technology and AI. Founded by tech visionaries John Furrier and Dave Vellante, SiliconANGLE Media has built a dynamic ecosystem of industry-leading digital media brands that reach 15+ million elite tech professionals. Its new proprietary theCUBE AI Video Cloud is breaking ground in audience interaction, leveraging theCUBEai.com neural network to help technology companies make data-driven decisions and stay at the forefront of industry conversations.

Press release: Casepoint selected by Elastic to modernize eDiscovery and legal hold. Casepoint has been selected by Elastic to provide enterprise eDiscovery and legal hold capabilities as the next step in its legal operations modernization, selecting the Casepoint platform for its technology fit and partnership approach. Date Published August 11, 2026 Reading Time WASHINGTON, August 11, 2026 - Casepoint, a leader in AI-powered legal, investigative, regulatory, compliance, and data discovery solutions for government agencies and enterprises, today announced that Elastic has standardized eDiscovery and legal hold on the Casepoint platform. The decision reflects Elastic's focus on operational maturity, risk reduction, and pragmatic technology adoption as the company scales, with Casepoint already helping the legal team reduce outside costs and find new ways to use legal data. Elastic selected Casepoint following a competitive RFP process that evaluated vendors against defined functional and technical requirements. Key requirements included strong support for Google Workspace and Slack, practical legal hold workflows, and a platform suited to the needs of a corporate legal department. After a rigorous evaluation, Elastic ultimately selected Casepoint for its ability to meet all of their requirements while simplifying complex workflows, as well as for Casepoint's partnership-driven approach. "Elastic's legal team is focused on building processes that match the needs of a growing, data-driven technology company," said Jen Lenander, Sr. Director & Chief of Staff at Elastic. "Casepoint stood out because it gave us the capabilities we needed to scale and handle more eDiscovery work directly, strengthen legal hold, and manage legal data more efficiently." Casepoint's partnership approach was also an important factor in Elastic's selection and implementation. The Casepoint team provided onboarding, training, technical setup, and business-case development, helping Elastic quickly apply the platform to both standard eDiscovery workflows and more creative legal operations use cases. "Technology fit was only part of the decision," said Lenander. "We also needed a partner that understood our goals, responded quickly, and helped us think through practical ways to use the platform. Casepoint has supported that approach from implementation through ongoing use." Beyond its original eDiscovery and legal hold needs, Elastic has already identified additional ways to use Casepoint to reduce outside costs and support internal analysis. In one DSAR-related matter, the platform helped Elastic export data in a usable format for work with a third-party provider, avoiding significantly higher third-party processing costs. Elastic also used Casepoint to convert contract-alias email data into a format that could be analyzed with an AI research tool, helping the legal team surface insights into contracting workflows without a separate consulting engagement. "Elastic approached this the right way, with a clear sense of what its legal team needed and a disciplined, unbiased evaluation process," said Pete Feinberg, Chief Product Officer at Casepoint. "That matters because more corporate legal teams are taking greater ownership of critical legal workflows, and they need technology that fits how they want to operate for peak efficiency." With Casepoint, Elastic now has a more controlled way to manage legal data, collaborate with internal and external teams, reduce outside costs, and support legal work across a modern technology environment. About Casepoint. Casepoint empowers government agencies and regulated enterprises to discover, secure, and act across their most critical legal, regulatory, and compliance workflows. Casepoint brings together 30+ years of deep government expertise with a decade of cloud-native eDiscovery innovation, serving 275+ federal civilian and defense agencies and enterprises - including the U.S. Department of War - and unifying legal hold, eDiscovery, investigations, FOIA, regulatory, and compliance workflows in one secure platform. Built on a cloud-native foundation with FedRAMP(R) High and DOD Impact Level 5 and 6 authorizations, Casepoint is an AI-forward platform that leverages assistive, predictive, and agentic AI, along with an open MCP for "bring your own agent" support. Every AI-driven decision is transparent and auditable, with human-in-the-loop governance built in. Backed by a white-glove, partnership-oriented approach to every customer relationship, Casepoint helps teams move faster, reduce risk, and maintain control under constant scrutiny. For more information, visit www.casepoint.com. Media Contact Carolyn Depko Plat4orm PR Media Relations Manager [email protected] 908-565-3709