What changed in this filing

/stocks — the workspaceLOADING

Item 1. Business

2026-06-08 compared with 2025-06-10 · 106 added, 103 removed, 314 unchanged (40% of the section changed)

2 unchanged sentences

AI, on the other hand, excels at analyzing complex patterns and generating insights, but it lacks the ability to find and access specific information within vast data stores.

Elastic’s Search AI Platform (“our platform”) combines the precision of search with the intelligence of AI to help our customers and community solve real-time business problems, unlock potential value, and achieve better outcomes.

The Elasticsearch Platform (“our platform”) combines the precision of search with the intelligence of AI to help our customers and community solve real-time business problems, unlock potential value, and achieve better outcomes.

Our platform, available as either a cloud service or a self-managed software, allows our customers to find insights and drive AI and machine learning use cases from large amounts of data.

We offer three Search AI-powered solutions—Elasticsearch, Elastic Observability, and Elastic Security—that are built on our platform.

We offer three Elasticsearch-powered solutions—Search & AI, Elastic Observability, and Elastic Security—that are built on our platform.

We help organizations, their employees, and their customers find what they need faster, while keeping mission-critical applications and infrastructure running smoothly and protecting against cyber threats.

As digital transformation continues to drive mission-critical business functions to the cloud, we believe that every company must incorporate search AI capabilities across IT and line-of-business organizations to find the answers that matter from all of its data in real time and at scale.

As digital transformation continues to drive mission-critical business functions towards increasingly complex data landscapes, we believe that every company must incorporate search AI capabilities across IT and line-of-business organizations to find the answers that matter from all of its data in real time and at scale.

Our platform is able to ingest data from any source, in any format, and perform search, analysis, and visualization of that data.

With Elasticsearch at its core, our platform is a highly scalable document store and search engine, and is the unified data store for all of our solutions and use cases.

Featuring a common, solution-agnostic user interface with powerful drag-and-drop visual analytics, centralized management capabilities, and the world's most downloaded open source vector database, our platform gives developers a full suite of sophisticated retrieval algorithms and the ability to integrate with large language models (“LLM”).

With Elasticsearch at its core, our platform is a highly scalable document store, columnar database, and search engine and is the unified data store for all of our solutions and use cases.

Featuring a common, solution-agnostic user interface with an embedded AI agent and support for third-party AI agents, our platform offers powerful drag-and-drop visual analytics, centralized management capabilities, and the world's most downloaded open source vector database, which gives developers a full suite of sophisticated retrieval algorithms and the ability to integrate with large language models (“LLM”).

It delivers the comprehensive set of capabilities developers need to build, maintain, and secure next-generation applications and services.

In addition, our out-of-the-box solutions (Elastic Observability and Elastic Security) deliver fast time-to-value for common use cases and, paired with our developer-centric platform which is extensible and customizable, allow us to innovate quickly and differentiate our offerings at every level.

We make our platform available as a service across major cloud providers (Amazon Web Services (“AWS”), Google Cloud Platform (“GCP”), and Microsoft (“Azure”)) in more than 55 public cloud regions globally.

We make our platform available as a service across major cloud providers (consisting of Amazon Web Services (“AWS”), Google Cloud Platform (“GCP”), and Microsoft Azure (“Azure”)) in more than 55 public cloud regions globally.

Customers can also deploy our platform across hybrid clouds, public or private clouds, and multi-cloud environments.

13 unchanged sentences

Because our business model provides access to all solutions with resource-based pricing, we make it easy for customers to expand across use cases.

Our business has experienced rapid growth around the world.

As of April 30, 2025, we had approximately 21,500 customers compared to approximately 21,000 customers and approximately 20,200 customers as of April 30, 2024 and 2023, respectively.

Our total revenue was $1.483 billion, $1.267 billion, and $1.069 billion for the years ended April 30, 2025, 2024, and 2023, respectively, representing year-over-year growth of 17% for the year ended April 30, 2025 and 19% for the year ended April 30, 2024.

Subscriptions accounted for 93% of our total revenue for the years ended April 30, 2025 and 2024, and 92% of our total revenue for the year ended April 30, 2023.

Our business has experienced significant growth around the world.

Our total revenue was $1.739 billion, $1.483 billion, and $1.267 billion for the years ended April 30, 2026, 2025, and 2024, respectively, representing year-over-year growth of 17% for the years ended April 30, 2026 and 2025.

Subscriptions accounted for 94% of our total revenue for the year ended April 30, 2026 and 93% of our total revenue for the years ended April 30, 2025 and 2024.

Revenue from customers located outside the United States accounted for 46%, 44%, and 42% of our total revenue for the years ended April 30, 2026, 2025, and 2024, respectively.

We recorded a net loss of $108.1 million for the year ended April 30, 2025, a net income of $61.7 million for the year ended April 30, 2024, and a net loss of $236.2 million for the year ended April 30, 2023.

We may incur net losses in the foreseeable future.

We recorded net income of $367.8 million for the year ended April 30, 2026, net loss of $108.1 million for the year ended April 30, 2025, and net income of $61.7 million for the year ended April 30, 2024.

We may incur net losses in the future.

Our net cash provided by operating activities was $326.9 million, $266.2 million, and $148.8 million for the years ended April 30, 2026, 2025, and 2024 respectively.

2 unchanged sentences

Our platform can be used by developers and IT decision makers to power a variety of use cases.

We also offer software solutions built on the Search AI Platform that address a wide variety of use cases.

Our platform and each of our solutions (Elasticsearch, Elastic Observability, and Elastic Security) are designed to run in public or private clouds, in hybrid environments, or in multi-cloud environments.

Elastic’s Search AI Platform

We also offer software solutions built on our platform that address a wide variety of use cases.

Our platform and each of our solutions (Search & AI, Elastic Observability, and Elastic Security) are designed to run as self-managed software or as a cloud service (in public or private clouds, in hybrid environments, or in multi-cloud environments).

Elasticsearch Platform

At its core, our platform is powered by Elasticsearch—a distributed, real-time vector database and analytics engine and data store for all types of data, including textual, numerical, geospatial, structured, and unstructured.

2 unchanged sentences

Elastic has spent years infusing its platform with a strong foundational suite of AI and machine learning capabilities—from support for external machine learning models to native vector search capabilities, supervised and unsupervised machine learning, and solution capabilities that improve search relevance and identify anomalies.

Elastic enables organizations to integrate generative AI and large language models by building key capabilities into its products.

Paid features enable capabilities such as automating anomaly detection on time-series data at scale through machine learning, facilitating compliance with data security and privacy regulations, supporting search across low-cost cold and frozen data tiers, and allowing real-time notifications and alerts.

Elastic enables organizations by providing the most complete data platform for context engineering and AI.

Our commitment to transparency and flexibility ensures that organizations have the visibility and control necessary to integrate AI into workflows with confidence.

Paid features enable capabilities such as automating anomaly detection on time-series data at scale through machine learning, generating embeddings using state-of-the-art models, and performing inference with LLMs.

Our platform further facilitates compliance with data security and privacy regulations, supporting search across low-cost cold and frozen data tiers, and allowing real-time notifications and alerts.

The source code of features included as part of our platform is generally visible to the public in the form of “open source.”

2 unchanged sentences

Our solutions include the following:

• Elasticsearch.

Our search solution provides a powerful foundation for building search AI-powered applications.

Key use cases for Elasticsearch include generative AI and retrieval-augmented generation, search applications, and foundational capabilities for building search experiences to support websites and portals, e-commerce, mobile app search, customer support, and workplace search.

• Search & AI.

Powered by Elasticsearch, Search & AI includes context engineering and AI, combining a scalable distributed data store, vector database, hybrid search, embedding and reranking AI models, and an agent builder.

Elasticsearch simplifies building search, AI, and agentic applications by unifying structured and unstructured data, along with vectors into a single, low-latency engine that delivers precise relevance.

Built for production, Elasticsearch scales with near real-time performance and cost efficiency, powering high-throughput ingestion and supporting petabyte-scale datasets.

• Elastic Observability.

Our observability solution enables unified analysis across the IT ecosystem of applications, networks, and infrastructure.

Our agentic observability platform brings logs, metrics, and traces into a unified datastore so SRE/Operations teams and AI agents can investigate, correlate, and resolve issues across applications, networks, and infrastructure.

Observability includes log analytics, to search, analyze, and visualize petabytes of structured and unstructured logs;

infrastructure monitoring, to gain visibility across cloud, on-premises, Kubernetes, serverless, and hosts;

Application Performance Monitoring (“APM”), to stream native production-grade OpenTelemetry without proprietary agents, and gain broad language support to deliver insight to pinpoint code issues and debug faster;

digital experience monitoring, to improve user experience with synthetic testing, real user monitoring (“RUM”), and uptime monitoring AI for IT operations (“AIOps”), always-on machine learning analysis that instantly surfaces anomalies, patterns, correlations, and root cause;

and LLM observability, to track latency, errors, prompts, responses, usage, and costs for all major LLM services.

infrastructure monitoring, for visibility across cloud, on-premises, Kubernetes, serverless, and hosts;

Application Performance Monitoring (“APM”), support for native production-grade OpenTelemetry without proprietary agents and broad language support to pinpoint code issues and debug faster;

digital experience monitoring, to improve user experience with synthetic testing and real user monitoring (“RUM”);

Streams, which parse and structure raw telemetry data without rebuilding pipelines and Significant Events, which surface critical errors, anomalies, and system changes, cutting time to root cause and giving AI agents the grounded context they need to triage alerts, run investigations, and propose remediations;

and LLM observability, to track latency, errors, prompts, responses, usage, and costs across major LLM services and agent frameworks.

• Elastic Security.

Our security solution provides unified protection to prevent, detect, and respond to threats.

Our Search AI-driven security analytics solution includes Security Information and Event Management (“SIEM”), with integrations to network, host, user, and cloud data sources.

Elastic Security enables investigations, incident management, shareable analytics, and workflow automation through Security Orchestration, Automation, and Response (“SOAR”);

and extended protection within SIEM with third party integrations and first party protections for both Endpoint Security (prevention, detection, and response);

and Cloud Security (cloud posture assessment, vulnerability management, and cloud workload protection).

Elastic Security is an agentic security operations platform where agents handle the full lifecycle from data ingestion through response, and human analysts handle judgment, verification, and approval.

Built on the Elasticsearch data and AI platform, it provides unified protection to prevent, detect, and respond to threats.

The solution combines Security Information and Event Management (“SIEM”), Extended Detection and Response (“XDR”), endpoint security with third-party integrations and first-party protections, cloud security, and native Security Orchestration, Automation, and Response (“SOAR”) capabilities in a single platform, with integrations across network, host, user, cloud, and endpoint data sources.

It enables investigations, incident management, shareable analytics, and workflow automation with AI-driven detection, investigation, and response.

Our Deployment Options

Our platform and our solutions can be deployed in public or private clouds, in hybrid environments, or in multi-cloud environments, to satisfy various user and customer needs.

Elastic Cloud, our family of cloud-based offerings (inclusive of both Elastic Cloud Hosted and Elastic Cloud Serverless), is hosted on major public cloud providers.

We also partner with other cloud providers that offer our software to users on their cloud platform as a hosted offering.

Users can also download and manage their own deployments of our platform and our solutions.

Our platform is available either as self-managed software or a cloud service.

With Elastic Self-Managed, users can also download and manage their own deployments of our platform and our solutions.

To help with more complex deployment scenarios, we offer paid proprietary products to deliver centralized provisioning, management, and monitoring across multiple deployments.

Elastic Cloud, our family of cloud-based offerings (including both Elastic Cloud Hosted and Elastic Cloud Serverless) is hosted on major public cloud providers.

We also partner with other cloud providers that offer our software to users on their cloud platform as a hosted offering.

Strengths of our Products

24 unchanged sentences

We continue to invest in our platform, solutions, and services to extend into new use cases, industries, geographies, and customers.

We regularly deliver new and enhanced capabilities to our customers, such as the enhanced AI technology now integrated in our platform, through regular releases, to which everyone has access based on our subscription model.

We continue to offer comprehensive Generative AI (“GAI”) capabilities in several key areas offering organizations tools and infrastructure to leverage GAI, including vector search capabilities, inference and retrieval APIs, embedding and relevance models, agentic workflows, data ingestion, data management, and domain-specific applications.

We view our Search AI capabilities as a major competitive differentiator for our products and intend to continue to invest in additional features and functionality related to AI.

We also recently released Elastic Cloud Serverless as an additional paid service offering for our customers.

We regularly deliver new and enhanced capabilities to our customers, such as the enhanced AI technology integrated in our platform, through regular releases, to which everyone has access based on our subscription model.

We continue to offer comprehensive AI capabilities in several key areas, providing organizations with tools and infrastructure to leverage AI, including vector search capabilities, inference and retrieval application programming interfaces (“APIs”), embedding and relevance models, agentic workflows, data ingestion, data management, and domain-specific applications.

We view our AI capabilities as a major competitive differentiator for our products and intend to continue to invest in additional features and functionality related to AI.

We also offer Elastic Cloud Serverless, a fully-managed, stateless architecture that auto-scales with customer usage.

We manage the underlying deployment and customers benefit from automatic upgrades.

Our technology investments include foundational platform capabilities as well as solution enhancements for our target use cases.

3 unchanged sentences

• Expand our customer base by acquiring new customers.

We engage our community and our partners to drive awareness and to invest in our sales and marketing team to grow our customer base.

Through Elastic Cloud, we provide the fastest and easiest way to get started with a free trial.

However, there is no free subscription tier in Elastic Cloud.

Self-managed users can easily download our software directly from our website and access many features free of charge, which also facilitates adoption.

We offer varied deployment options to cater to a wide range of customer use cases.

We engage our community and our partners to drive awareness and invest in our sales and marketing team to grow our customer base.

We offer varied deployment options, including Elastic Self-Managed, Elastic Cloud Hosted, and Elastic Cloud Serverless, to cater to a wide range of customer use cases.

Our sales and marketing team conducts campaigns to drive further awareness and adoption within the user community.

As a result, many of our sales prospects, including those in executive-level conversations, are already familiar with our technology prior to entering into a commercial relationship with us.

As a result, many of our sales prospects, including those in executive-level conversations, are already familiar with our technology before entering into a commercial relationship with us.

Additionally, we leverage our network of partners to drive awareness and expand our sales and marketing reach to target new customers.

2 unchanged sentences

We view initial success with our products as a path to drive expansion to new use cases and projects and larger deployments within organizations.

We often enter an organization through a single developer or a small team for an initial project or use case with an objective to quickly solve a technical challenge or business problem.

Because of the rapid success with our products, knowledge of Elastic often spreads within an organization to new teams of developers, architects, IT operations personnel, security personnel, and senior executives, leading to more use cases for our products and solutions, and larger deployments at higher subscription tier levels.

• Increase usage of Elastic Cloud.

As users and customers increasingly want to consume highly-scalable cloud solutions, we believe that Elastic Cloud continues to represent a significant growth opportunity.

We plan to continue to invest resources in driving further innovation and increasing the adoption of Elastic Cloud.

We recently launched a new Elastic Cloud Serverless offering that simplifies operational management of our platform, delivering easier onboarding and autoscaling across security, observability, and search solutions.

We often enter an organization through a single use case or solution.

• Expand our penetration in enterprise and commercial customer accounts.

Using a sales-led motion, we continue to target strategic enterprise and high-propensity commercial customers with our sales teams.

We meet our customers where they are, selling Elastic Self-Managed, Elastic Cloud Hosted, and Elastic Cloud Serverless deployments, focusing on high-value existing and new customers.

• Expand our strategic and regional partnerships.

7 unchanged sentences

As of April 30, 2026, we had approximately 24,000 customers compared to approximately 21,500 and approximately 21,000 customers as of April 30, 2025 and 2024, respectively.

One customer, a channel partner, accounted for 12% of total revenue for the year ended April 30, 2025 and 11% of total revenue for the year ended April 30, 2024.

No customer accounted for 10% or more of our total revenue for the year ended April 30, 2023.

We focus on higher-value customers as exemplified by accounts spending more than $100,000 and $1.0 million annually.

As of April 30, 2026, we had more than 1,720 customers spending more than $100,000 annually, and more than 240 customers spending more than $1.0 million annually.

One customer, a channel partner, accounted for 11% of total revenue for the years ended April 30, 2026 and 2024, and 12% of total revenue for the year ended April 30, 2025.

We have experienced quarterly fluctuations and seasonality in our sales and results of operations based on our entry into agreements with new and existing customers, customer usage patterns for our consumption-based arrangements, and the mix between annual and monthly contracts entered into in each reporting period.

8 unchanged sentences

Our software development process is based on iterative releases of our platform.

We are organized in small functional teams with a high degree of autonomy and accountability.

We are organized in small functional teams with a high degree of autonomy and accountability, leveraging AI software development tools to accelerate our time-to-market.

Our distributed and highly modular team structure and well-defined software development processes also allow us to successfully incorporate acquired technologies.

4 unchanged sentences

With our business model, where users can download and use many of our features free of charge, our sales prospects are often already familiar with or using our platform.

We conduct low-touch campaigns to keep users and customers engaged once they have begun using Elastic Cloud or have downloaded our software.

We conduct low-touch campaigns to keep users and customers engaged once they have begun using our software.

This process includes providing high-quality content, documentation, webinars, videos, and blogs through our website.

We also drive high-touch engagement with qualified prospects and customers to drive further awareness, adoption, and expansion of our products with paid subscriptions.

The majority of our new customers use Elastic Cloud.

Many of these customers start with limited initial spending on our products but can significantly increase their spending over time.

8 unchanged sentences

We work with many of the major cloud providers to increase awareness of our products and make it easy to access our software.

We partner with Amazon, Google, and Microsoft to offer Elastic Cloud on AWS, GCP, and Microsoft Azure, respectively, through direct purchase from us or their respective marketplaces.

We partner with Amazon, Google, and Microsoft to offer Elastic Cloud on AWS, GCP, and Azure, respectively, through direct purchase from us or their respective marketplaces.

We also partner with other cloud providers to offer our free and paid proprietary features to users on their cloud platforms.

9 unchanged sentences

Our AI ecosystem provides customers with a curated, comprehensive set of AI technologies and tools integrated with the Elasticsearch vector database, designed to speed time-to-market, ROI delivery, and innovation.

The Elastic AI Ecosystem includes integrations with Anthropic's Claude, Cohere, Confluent, Dataiku, DataRobot, Galileo, Hugging Face, LangChain, LlamaIndex, Mistral AI, NVIDIA, OpenAI, Protect AI, RedHat, Vectorize.io, and Unstructured, along with all of the major hyperscalers, consisting of Amazon Web Services (AWS), Google Cloud, and Microsoft.

The Elastic AI Ecosystem includes integrations with Anthropic's Claude, Cohere, Confluent, Dataiku, DataRobot, Galileo, Hugging Face, LangChain, LlamaIndex, Mistral AI, NVIDIA, OpenAI, Protect AI, Red Hat, Vectorize.io, and Unstructured, along with all of the major hyperscalers, consisting of AWS, GCP, and Azure.

We offer consulting and training to assist customers in accelerating their success with our software.

10 unchanged sentences

Our Technology

Our platform consists of our three solutions (Elasticsearch, Elastic Observability, and Elastic Security), and software that supports our various deployment alternatives.

Our platform consists of our three solutions (Search & AI, Elastic Observability, and Elastic Security) and software that supports our various deployment alternatives.

Because our solutions are built on top of a common platform, innovations and new capabilities in our platform may benefit many of our solutions.

Our customers can customize and extend our solutions to fit their needs by leveraging the power of our platform and our developer capabilities.

Technology Features of Elastic’s Search AI Platform

Technology Features of the Elasticsearch Platform

Key features of our platform include the following:

4 unchanged sentences

Elasticsearch is the most downloaded open source vector database, allowing users to create, store, and search vector embeddings at scale.

By adding the ability to combine text and vector search for hybrid retrieval—and filtering, ranking, and re-ranking capabilities to deliver the most relevant results—we go beyond traditional vector databases.

Elastic has the only platform with Better Binary Quantization to reduce the memory required without sacrificing accuracy, and provide native integrations to the leading AI providers.

• Retrieval Augmented Generation (“RAG”).

Customers use Elasticsearch to build generative AI applications on private data.

RAG enables them to ground LLMs on a specific corpus of data without needing to train or fine-tune models.

Elasticsearch excels at producing the most relevant context for grounding LLMs using RAG, while also delivering enterprise-grade security based on document and field-level permissions that ensure data privacy and security.

When using RAG with Elastic, customers also benefit from built-in tools and models that cover the entire RAG workflow from ingest and inference to retrieval and LLM integration, giving developers everything they need to build RAG-based applications.

By adding the ability to combine text and vector search for hybrid retrieval—and filtering, ranking, and reranking capabilities to deliver the most relevant results—we go beyond traditional vector databases.

Elastic is the only platform with Better Binary Quantization to reduce the memory required without sacrificing accuracy.

• Agent Builder.

Elastic Agent Builder is an AI conversational capability that lets you create AI agents that answer questions and take actions over any customer data using natural language.

Agents combine LLM reasoning and context engineering with built-in and custom tools that query customer data, so responses are grounded in customer context.

• Machine learning, AI, and alerting.

Machine learning capabilities such as anomaly detection, forecasting, and categorization are a tightly integrated part of our platform so as to automatically model the behavior of data, such as trends and periodicity, in real time, to identify issues faster, streamline root cause analysis, and reduce false positives.

Without these capabilities, it can be very difficult to identify issues such as infrastructure problems or intruders in real time across complex, high-volume, fast-moving datasets.

Without these capabilities, it can be difficult to identify issues such as infrastructure problems or intruders in real time across complex, high-volume, fast-moving datasets.

In the last few years, we have also added native support for vector search and model management for advanced machine learning models.

5 unchanged sentences

• Developer centricity.

Elasticsearch has consistent, well-documented application programming interfaces (“APIs”) that work the same way on one node during initial development as on a hundred nodes in production.

Elasticsearch has consistent, well-documented APIs that work the same way on one node during initial development as on a hundred nodes in production.

Elasticsearch also ships with a number of language clients that provide a natural way to integrate with a variety of popular programming frameworks, reducing the learning curve, and leading to a shorter time to realizing value.

5 unchanged sentences

Elasticsearch is designed to scale horizontally and be resilient to node or hardware failures.

As nodes join a cluster, data is automatically re-balanced and queries and indexing are spread across the new nodes seamlessly.

As nodes join a cluster, data is automatically rebalanced and queries and indexing are spread across the new nodes seamlessly.

This makes it easy to add hardware to increase indexing throughput or improve query throughput.

8 unchanged sentences

Kibana, our platform’s user interface, allows users to manage our platform and to visualize data.

Additionally, the interfaces for many of our solutions (e.g., Elastic Observability and Elastic Security) are built into this interface.

Customers can also use Agent Builder’s chat interface to communicate in real time with their data.

Additionally, the interfaces for many of our solutions (such as Elastic Observability and Elastic Security) are built into this interface.

Key features of our user interface include the following:

4 unchanged sentences

Our platform’s user interface query, filtering, and data summarization capabilities reflect Elasticsearch’s powerful query domain-specific language and aggregation framework while making it interactive.

• Management of the Search AI Platform.

• Management of the Elasticsearch Platform.

Our user interface illustrates the health of our platform’s various components and provides timely alerts to notify administrators of any problems.

2 unchanged sentences

Our user interface is where our users and customers access our three solutions:

Elasticsearch, Elastic Observability, and Elastic Security.

Search & AI, Elastic Observability, and Elastic Security.

It provides core services, like security, alerting, and data visualization components, which make it easy for users to discover all of the capabilities our platform and solutions provide.

6 unchanged sentences

The functionality of our solutions often includes specialized data collection, through standardized APIs or custom agents, and custom user interfaces for specific data analytics, visualizations, workflows, and actions.

Elasticsearch gives users the tools to improve customer search experiences quickly and scale them seamlessly.

Search & AI gives users the tools to improve customer search experiences quickly and scale them seamlessly.

• Search applications.

Customers can bring the focused power of our platform to their company website, ecommerce site, or applications with sophisticated retrieval algorithms and the ability to integrate with large language models.

Customers can bring the focused power of our platform to their company website, ecommerce site, workplace search, or applications with sophisticated retrieval algorithms and the ability to integrate with LLMs.

Elastic delivers seamless scalability, tunable relevance controls, thorough documentation, well-maintained clients, a refined set of APIs, intuitive dashboards, and robust analytics to build a leading search experience.

Customers can build rich applications directly on top of Elasticsearch, or they can use our Application Search framework to rapidly build and customize search applications.

• Workplace search.

Customers can deploy internal workplace search to bring modern search to collaborative decisions and experiences.

Elastic seamlessly connects to some of the world’s most widely adopted productivity tools, customer relationship management platforms, cloud storage platforms, collaboration tools, operation management platforms, and content management systems.

Custom sources provide a set of APIs that let customers and users ingest any type of content from even more sources while preserving access control information.

Customers can build rich applications directly on top of Elasticsearch, or they can use our Application Search framework to rapidly build and customize search applications, including internal workplace search-based experiences.

• Context engineering.

Customers use Elasticsearch to build context engines that ground LLMs and AI agents in company-specific information for trustworthy, precise, and cost-efficient outcomes.

Elastic unifies enterprise data—structured, unstructured, and vectors—to give LLMs and AI agents the right information at the right time, whether they are powering retrieval-augmented generation pipelines or autonomous workflows.

Through Jina AI's multi-modal, multi-lingual embedding models, semantic reranking, and hybrid search across BM25, kNN, and dense vector retrieval, Elastic turns logs, documents, telemetry, and transactions into highly relevant context that AI agents and LLMs can act on with fewer tokens consumed.

Elastic Observability monitors the IT ecosystem of applications, services, and infrastructure to deliver actionable insights into performance and availability.

5 unchanged sentences

With 500+ out-of-the-box integrations and automatic import, users gain visibility across cloud, Kubernetes, serverless, on-premises, and hosts.

Intuitive visualizations and quick analysis supported by out-of-the-box machine learning and preconfigured dashboards allow users to troubleshoot faster, as well as measure performance targets for services such as availability, latency, traffic, and errors using Service Level Objectives (“SLO”).

OpenTelemetry-based APM delivers insights into application performance at the code level.

11 unchanged sentences

Elastic delivers fast, scalable detection and investigation across cloud, network, endpoint, user, and third-party data.

Security data is normalized using Elastic Common Schema (“ECS”) and enriched to provide relevant context for analysis.

Security data is normalized using Elastic Common Schema and enriched to provide relevant context for analysis.

Analysts can search across all data, pivot during investigations, and review activity using timeline views and built-in case tracking.

1 unchanged sentence

The platform is open and accessible, giving teams full control over their data and the flexibility to adapt detections and workflows.

Built-in SOAR capabilities streamline response by automating alert forwarding, case creation, and workflow integrations with external tools, reducing manual effort without switching platforms.

• Endpoint security.

Elastic Security includes endpoint detection and response capabilities integrated directly into the SIEM.

These capabilities detect and block ransomware, fileless attacks, and hands-on-keyboard activity—even on isolated hosts.

Endpoint data, whether native or from third-party tools, can be analyzed alongside other telemetry to provide context and trigger automated response actions across systems.

Built-in SOAR capabilities streamline response by automating alert forwarding, case creation, and workflow integrations with external tools, thus reducing manual effort without switching platforms.

Elastic delivers XDR capabilities by correlating data across endpoints, cloud, network, and user activity, all within the SIEM.

1 unchanged sentence

By analyzing native and third-party telemetry together in one interface, Elastic reduces investigation time and eliminates context switching.

• Endpoint security.

Elastic Security includes endpoint detection and response capabilities integrated directly into the SIEM.

These capabilities detect and block ransomware, fileless attacks, and hands-on-keyboard activity, including on isolated hosts.

Endpoint data, whether native or from third-party tools, is analyzed alongside other telemetry to provide context and trigger automated response actions across systems.

• Cloud security.

Elastic provides cloud detection and response capabilities directly within the SIEM, giving security teams visibility into activity across multi-cloud environments.

It combines cloud workload monitoring with posture and vulnerability context.

Native telemetry from cloud providers and findings from third-party CSPM tools can be ingested and analyzed together, helping teams connect misconfigurations to real-time threats.

These capabilities combine cloud workload monitoring with posture and vulnerability context.

Native telemetry from cloud providers and findings from third-party cloud security posture management tools can be ingested and analyzed together, helping teams connect misconfigurations to real-time threats.

This unified view across accounts and providers reduces blind spots and speeds up response to risks in modern cloud environments.

• Workflows for security.

Elastic Workflows brings native automation directly into Elastic Security, delivering SOAR capabilities without a separate tool.

It combines scripted playbooks for defined tasks with AI agents that reason through complex investigations and execute response actions including isolating hosts, querying threat intelligence, and escalating incidents.

Workflows for security connects to external systems including Slack, Jira, ServiceNow, and PagerDuty, with representational state transfer (“REST”) API support for additional tools, to coordinate response across the security stack.

Elastic has always been committed to an open development process with transparent and direct engagement with our community.

Our team extends beyond our employee base and includes all the users who download our software.

Our users interact with us on our website forums and on X (formerly known as Twitter), GitHub, Stack Overflow, Quora, Facebook, and other platforms.

Our team extends beyond our employee base and includes all of the users who download our software.

Our users interact with us on our website forums and on X, GitHub, Stack Overflow, Quora, Facebook, and other platforms.

To build products that best meet our users’ needs, we focus on, and invest in, building a strong community.

8 unchanged sentences

Our principal competitors include:

• For Elasticsearch and other platform use cases:

offerings such as Apache Solr (open source offering), Lucidworks Fusion, and MongoDB Atlas, and search tools including Algolia, Coveo, Google, Pinecone, and Microsoft Azure Cognitive Search.

• For Search & AI:

providers of traditional search offerings, such as Algolia, Apache Solr (open source offering), and Coveo;

native vector databases, such as Pinecone, Qdrant, and Weaviate;

database platforms with integrated vector search, such as MongoDB Atlas;

and search tools, such as Google Gemini Enterprise Agent Platform (formerly Vertex AI) and Microsoft Azure AI Search.

• For Elastic Observability:

software vendors with specific observability solutions, such as AppDynamics (owned by Cisco Systems), Datadog, Dynatrace, New Relic, and Splunk (owned by Cisco Systems).

software vendors with specific observability solutions, such as AppDynamics and Splunk (each owned by Cisco Systems), Datadog, Dynatrace, and New Relic.

• For Elastic Security:

security vendors such as Azure Sentinel (by Microsoft), CrowdStrike, Google SecOps, Palo Alto Networks.

and Splunk (owned by Cisco Systems).

• Certain cloud hosting providers and managed service providers, including AWS, which offer products or services based on a forked version of our platform.

security vendors, such as Azure Sentinel (owned by Microsoft), CrowdStrike, Google SecOps, Palo Alto Networks, and Splunk (owned by Cisco Systems).

• Certain cloud hosting providers and MSPs, including AWS, which offer products or services based on a forked version of our platform.

These offerings are not supported by Elastic and come without any of Elastic’s proprietary features, whether free or paid.

20 unchanged sentences

We may also expand into new markets and encounter additional competitors in such markets.

While our products and solutions have various competitors across different use cases, such as search applications and workplace search, logging, metrics, APM, business analytics and security analytics, we believe that few competitors currently have the capabilities to address our entire range of use cases.

We believe our industry requires constant change and innovation, and we plan to continue to evolve search as a foundational technology to solve the problems of today and new emerging problems in the future.

While our products and solutions have various competitors across different use cases, such as search applications and workplace search, logging, metrics, APM, and business and security analytics, we believe that few competitors currently have the capabilities to address our entire range of use cases.

Intellectual Property

5 unchanged sentences

The laws, procedures and restrictions on which we rely may provide only limited protection, and any of our intellectual property rights may be challenged, invalidated, circumvented, infringed, or misappropriated.

In addition, the laws of certain countries do not protect proprietary rights to the same extent as the laws of the United States or other jurisdictions, and we therefore may be unable to protect our proprietary technology in certain jurisdictions.

In addition, the laws of certain countries do not protect proprietary rights to the same extent as the laws of the United States, the Netherlands, or other jurisdictions and, therefore, we may be unable to protect our proprietary technology in certain jurisdictions.

In addition, our technology incorporates software components licensed to the general public under open source software licenses such as the Apache Software License Version 2.0 (“Apache 2.0”) and other permissive licenses.

17 unchanged sentences

Elastic originated as a distributed company and continues to be distributed by design.

We have built our processes, systems, and teams so that employees can generally perform their jobs without needing to be physically present in the same room—or even in the same time zone—as their colleagues.

We have built our processes, systems, and teams so that employees can generally perform their jobs without needing to be physically present at the same location as their colleagues.

Just as distributed systems are more resilient, we believe that a distributed workforce helps build a strong company that can scale and adapt as new challenges arise.

3 unchanged sentences

We endeavor to be an employer of choice and strive to sustain a sense of inclusion and belonging among all employees with programs designed to foster community and an appreciation for the unique experiences and perspectives represented across Elasticians globally.

We are committed to ensuring that our employees have a voice and the opportunity to share their ideas and insights.

We formally seek employee feedback through regular employee experience surveys, and the results of these surveys are reviewed at the company, functional, team, and manager level.

We are committed to ensuring that our employees have a voice and the opportunity to share their ideas and insights through regular employee experience surveys reviewed across multiple organizational levels.

We support the continuous learning and development of all Elasticians through programs that develop skills for individual contributors, leaders of others, and leaders of the business.

12 unchanged sentences

See “Item 1A.

Risk Factors” of this Annual Report on Form 10-K for a discussion of these potential impacts.

Risk Factors” in this Annual Report on Form 10-K for a discussion of these potential impacts.

Corporate Information

13 unchanged sentences

Compared sentence by sentence after normalising whitespace, quotation marks, case and digits, so re-formatting and restated figures do not read as changed language. Wording changes appear as one removal and one addition. The current filing and the prior one are authoritative.

What changed 10-K

Item 1. Business