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Item 1. Business

2025-06-10 compared with 2024-06-14 · 204 added, 258 removed, 213 unchanged (68% of the section changed)

Elastic, the Search AI Company, enables our customers to find the answers they need in real time, using all of their data, at scale.

The Elastic Search AI Platform (“our platform”), combines the power of search with AI to help companies solve real-time business problems, unlock potential value, and achieve better outcomes.

Our platform, available as both a hosted, managed service across public clouds as well as 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-powered solutions – Search, Observability, and Security – that are built on the platform.

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

As digital transformation drives 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.

Our platform is built on the Elastic Stack, a powerful set of software products that ingest data from any source, in any format, and perform search, analysis, and visualization of that data.

At the core of the Elastic Stack is Elasticsearch - a highly scalable document store and search engine, and the unified data store for all of our solutions and use cases.

Another component of the Elastic Stack is Kibana, which delivers a common user interface across all of our solutions, with powerful drag-and-drop visual analytics, and centralized management of the platform.

Our platform also includes the Elasticsearch Relevance Engine™ (“ESRE”), which combines advanced AI with Elastic’s text search to give developers a full suite of sophisticated retrieval algorithms and the ability to integrate with large language models.

Our out-of-the-box solutions 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 fast and differentiate our offerings at every level.

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

Elastic, the Search AI Company, enables its customers to transform data into answers, actions, and outcomes with Search AI.

While search technology revolutionized information retrieval through its ability to instantly return relevant results from massive datasets, it struggles when it comes to understanding context and generating insights.

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.

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 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.

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”).

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.

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

Our business model is based primarily on a combination of a paid Elastic-managed hosted service offering and paid and free proprietary self-managed software.

Our business model is based primarily on a combination of paid service offerings (Elastic Cloud Hosted and Elastic Cloud Serverless) and free and paid proprietary self-managed software (Elastic Self-Managed).

Our paid offerings for our platform are sold via subscription through resource-based pricing, and all customers and users have access to varying levels of features across all solutions.

In Elastic Cloud, our family of cloud-based offerings, we offer various subscription tiers tied to different features.

For users who download our software, we make some of the features of our software available free of charge, allowing us to engage with a broad community of developers and practitioners and introduce them to the value of the Elastic Stack.

We believe in the importance of an open software development model, and we develop the majority of our software in public repositories as open code under a proprietary license.

We believe in the importance of an open software development model, and we develop the majority of our software in public repositories under an open source GNU Affero General Public License v3 (“AGPL”) license, as well as under a proprietary license.

Unlike some companies, we do not build an enterprise version that is separate from our free distribution.

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All of these actions help us build a powerful commercial business model that we believe is optimized for product-driven growth.

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

The core of Elasticsearch and Kibana (a user interface) are open source under an AGPL license, and our open source code is housed in public repositories.

Our customers often significantly expand their usage of our products and services over time.

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Our business has experienced rapid growth around the world.

As of April 30, 2024, we had approximately 21,000 customers compared to approximately 20,200 customers and over 18,600 customers as of April 30, 2023 and 2022, respectively.

Our total revenue was $1.267 billion, $1.069 billion, and $862.4 million for the years ended April 30, 2024, 2023 and 2022, respectively, representing year-over-year growth of 19% for the year ended April 30, 2024 and 24% for the year ended April 30, 2023.

Subscriptions accounted for 93%, 92% and 93% of our total revenue for the years ended April 30, 2024, 2023 and 2022, respectively.

Revenue from outside the United States accounted for 42%, 41% and 44% of our total revenue for the years ended April 30, 2024, 2023 and 2022, respectively.

While we recorded net income of $61.7 million for the year ended April 30, 2024, we incurred net losses of $236.2 million and $203.8 million for the years ended April 30, 2023 and 2022, respectively.

Although we recorded net income for the year ended April 30, 2024, we expect to incur net losses for the foreseeable future.

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.

Revenue from customers located outside the United States accounted for 44%, 42%, and 41% of our total revenue for the years ended April 30, 2025, 2024, and 2023, 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.

Our net cash provided by operating activities was $266.2 million, $148.8 million, and $35.7 million for the years ended April 30, 2025, 2024, and 2023 respectively.

Our products enable our customers and users to find relevant information and insights nearly instantly in large amounts of data across a broad range of business and consumer use cases.

We offer the Elastic Stack, a powerful set of software products that ingest and store data from any source, in any format, and perform search, analysis, and visualization, usually in milliseconds.

The Elastic Stack can be used by developers and IT decision makers to power a variety of use cases.

We also offer software solutions built in the Elastic Stack that address a wide variety of use cases.

The Elastic Stack and our solutions are designed to run in public or private clouds, in hybrid environments, or in multi-cloud environments.

The Elastic Stack

The Elastic Stack is primarily composed of the following products:

• Elasticsearch.

Elasticsearch is the heart of the Elastic Stack.

It is a distributed, real-time vector search and analytics engine and data store for all types of data, including textual, numerical, geospatial, structured, and unstructured.

Kibana is the user interface for the Elastic Stack.

It is the visualization layer for data stored in Elasticsearch.

It is also the management and configuration interface for all parts of the Elastic Stack.

Elastic has spent years infusing both Elasticsearch and Kibana with a foundation of AI and machine learning built on ESRE, 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.

Our platform includes a powerful set of solutions able to ingest and store data from any source, in any format, and perform search, analysis, and visualization, usually in milliseconds.

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

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.

Our platform includes a user interface (known as “Kibana”) that is the visualization layer for data stored in Elasticsearch;

this layer is also the management and configuration interface for all parts of our platform.

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.

The Elastic Stack also supports data ingest with a number of products:

• Elastic Agent.

Elastic Agent is a single, unified way to add monitoring for logs, metrics, and other types of data to each host.

Elastic Agent includes integrated host protection and central management.

Beats is the family of lightweight, single-purpose data shippers for sending data from edge machines to Elasticsearch or Logstash.

Logstash is the dynamic data processing pipeline for ingesting data into Elasticsearch or other storage systems from a multitude of sources simultaneously.

Paid proprietary features in the Elastic Stack 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.

The source code of features in the Elastic Stack is generally visible to the public in the form of “open code.”

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.

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

Our Solutions

We have built a number of solutions into the Elastic Stack to make it easier for organizations to use our software for common use cases.

We have built a number of solutions into our platform to make it easier for organizations to use our software for common use cases.

Our solutions include the following:

Our Search solution provides a powerful search platform for building search AI applications.

Key use cases for Search 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.

• Observability.

• 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.

• Elastic Observability.

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

Observability includes:

Logs, to search and analyze petabytes of structured and unstructured logs;

Metrics, to search and analyze numeric and time series data;

Application Performance Monitoring (“APM”), to deliver insight into application performance and health metrics and provide developers with confidence in their code;

and Synthetic Monitoring, to proactively monitor the availability and functionality of user journeys.

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.

• Elastic Security.

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

Our AI-driven security analytics solution includes:

Security Information and Event Management (“SIEM”), with integrations to network, host, user, and cloud data sources, as well as workflow and operations, shareable analytics, incident management, and investigations;

extended protection with both third party integrations as well as first party protections for both Endpoint Security (prevention, detection, and response) and Cloud Security (cloud posture assessment, vulnerability management, and cloud workload protection).

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).

Our Deployment Options

The Elastic Stack 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, is hosted on major public cloud providers.

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

Users can also download and manage their own deployments of the Elastic Stack and our solutions.

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.

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

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The strengths of our products include the following:

The Elastic Stack can find matches for search criteria in milliseconds within even the largest structured and unstructured datasets.

Our platform can find matches for search criteria in milliseconds within even the largest structured and unstructured datasets.

Its schemaless structure and inverted indices enable real-time search of high volumes of structured, unstructured, and time series data.

The Elastic Stack is a distributed system and can scale massively.

Our platform is a distributed system and can scale.

It has the ability to subdivide search indices into multiple pieces called shards, which enables data volume to be scaled horizontally and operations to be distributed across hundreds of systems or more.

A developer running hundreds of nodes has the same user experience as a developer running a single node on a laptop.

Elasticsearch uses multiple analytical techniques, including both traditional and AI-powered relevance techniques, to determine the similarity between stored data and queries, generating highly relevant results reflecting a deep understanding of text and context.

Our platform uses multiple analytical techniques, including both traditional and AI-powered relevance techniques, to determine the similarity between stored data and queries, generating highly relevant results reflecting a deep understanding of text and context.

Its sophisticated yet developer-friendly query language permits advanced search and analytics.

Additionally, the speed of the Elastic Stack permits query iteration, further enhancing the relevance of search results.

Additionally, the speed of our platform permits query iteration, further enhancing the relevance of search results.

• Ease of Use.

The Elastic Stack is engineered to take a user from data to dashboard or inquiry to insight in minutes.

Our platform is engineered to take a user from data to dashboard or inquiry to insight in minutes.

It offers an easy getting-started experience, featuring streamlined download and deployment, sensible defaults, a simple and intuitive query language, and no need to define a schema up front.

Administrative tasks such as securing the Elastic Stack are intuitive and integrated into the user experience, as are investigative tasks such as data visualization.

Administrative tasks such as securing the platform are intuitive and integrated into the user experience, as are investigative tasks such as data visualization.

• Flexibility.

The Elastic Stack is able to ingest, filter, store, search, and analyze data in any form, whether structured or unstructured.

These capabilities enable the Elastic Stack to generate insights from a wide variety of data sources for a broad range of use cases.

The flexibility of the Elastic Stack also enables users to begin using our products along with their existing systems, which lowers barriers to adoption.

Our platform is able to ingest, filter, store, search, and analyze data in any form, whether structured or unstructured.

These capabilities enable our platform to generate insights from a wide variety of data sources for a broad range of use cases.

The flexibility of our platform also enables users to begin using our products along with their existing systems, which lowers barriers to adoption.

• Extensibility.

Developers can use the Elastic Stack as a foundation for addressing a wide variety of use cases.

Our open approach to building the Elastic Stack empowers developers to innovate and utilize it to fit their specific needs.

Additionally, our developer community actively engages with us to improve and expand the Elastic Stack.

Our platform can be used by developers as a foundation for addressing a wide variety of use cases.

Our open approach to building our platform empowers developers to innovate and utilize it to fit their specific needs.

Additionally, our developer community actively engages with us to improve and expand our platform.

Our Growth Strategies

We pursue the following growth strategies:

• Increase usage of Elastic Cloud.

As users and customers increasingly want to consume highly-scalable cloud solutions, we believe that Elastic Cloud represents 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 in technical preview that simplifies operational management of our platform, delivering easier onboarding and autoscaling across security, observability, and search solutions.

• Extend our product leadership through continued investment in our technology.

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.

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

• Increase product adoption by improving ease of use and growing our user community.

With our engineering efforts focused on the user experience, we will continue to develop software that makes our products easier to use and adopt for both developers and non-developers.

We will continue to engage with developers globally to grow our user community through a wide range of touch points such as community meetups, global community groups, hackathons, our global events, our user conferences, which we call ElasticON, and engagement on our website, user forums, and code repositories.

With our engineering efforts focused on the user experience, we continue to develop software that makes our products easier to use and adopt for both developers and non-developers.

We plan to continue to engage with developers globally to grow our user community through a wide range of touch points such as community meetups, global community groups, hackathons, our global events, our user conferences, which we call ElasticON, and engagement on our website, user forums, and code repositories.

• Expand our customer base by acquiring new customers.

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

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.

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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.

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 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 prior to 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.

• Expand within our existing customer base through new use cases and larger deployments.

We will continue to invest in helping users and customers be successful with our products.

We continue to invest in helping users and customers be successful with our products.

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.

• Extend our product leadership through continued investment in our technology.

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

We regularly deliver new and enhanced capabilities to our customers through regular releases, to which everyone has access based on our subscription model.

Our technology investments within the Elastic Stack include foundational capabilities as well as solution enhancements for our target use cases.

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.

• Expand our strategic and regional partnerships.

We will continue to pursue partnerships to further the development of the Elastic Stack and our customer reach.

Our partners assist us in driving awareness of Elastic and our products, using the Elastic Stack to address customer requirements, and extending our reach in geographic areas and verticals where we do not have a formal sales presence.

We continue to pursue partnerships to further the development of our platform and our customer reach.

Our partners assist us in driving awareness of Elastic and our products, using our platform to address customer requirements, and extending our reach in geographic areas and verticals where we do not have a formal sales presence.

• Selectively pursue strategic acquisitions.

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Organizations of all sizes, across many industries, including enterprises, educational institutions and government entities, purchase our products for a variety of use cases.

As of April 30, 2024, we had approximately 21,000 customers compared to approximately 20,200 customers and over 18,600 customers as of April 30, 2023 and 2022, respectively.

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

No customer accounted for 10% or more of our total revenue for the years ended April 30, 2023 and 2022.

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

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We intend to continue to invest in our research and development capabilities to extend our products.

Research and development expense totaled $342.0 million and $313.5 million for the years ended April 30, 2024 and 2023, respectively.

Research and development expense totaled $365.8 million, $342.0 million, and $313.5 million for the years ended April 30, 2025, 2024, and 2023, respectively.

We plan to continue to devote significant resources to research and development.

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With a globally distributed engineering team, we are able to recruit, hire, and retain high-quality, experienced developers, technology leads, and product managers, and operate at a rapid pace to drive product releases, fix bugs, and create new product offerings.

Our software development process is based on iterative releases of the Elastic Stack.

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.

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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, through direct purchase from us or their respective marketplaces.

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

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• OEM and MSP partners.

Our original equipment manufacturing (“OEM”) and managed service provider (“MSP”) partners embed an Elastic subscription into the products or services they offer to their customers.

OEM or MSP partners are able to include Elastic’s proprietary features in their product, receive ongoing support from Elastic for product development, and receive support for end customer issues related to Elastic.

Our OEM and MSP partners embed an Elastic subscription into the products or services they offer to their customers.

OEM and MSP partners are able to include Elastic’s proprietary features in their product, receive ongoing support from Elastic for product development, and receive support for end customer issues related to Elastic.

• Technology partners.

Our technology partners collaborate with Elastic to create a standardized solution for end users that includes technology from both Elastic and the partner.

Technology partners represent a deeper collaboration than community contributions and are distinct from distribution-oriented relationships like OEMs and MSP partners.

Technology partners represent a deeper collaboration than community contributions and are distinct from distribution-oriented relationships like OEM and MSP partners.

• AI ecosystem.

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.

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

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Customer Support

We endeavor to make it easy for users to download, install, deploy and use the Elastic Stack and our solutions.

We endeavor to make it easy for users to download, install, deploy, and use our platform and our solutions.

Our user community enables users to engage in self-help and collaboration.

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Our support team is globally distributed and provides coverage 24 hours per day, 365 days per year, across multiple languages.

We do not sell support separately and, as such, it is only available for customers who license one or more of our product offerings.

We do not sell support independently and, as such, it is only available for customers who license one or more of our product offerings.

Our Technology

Our platform consists of the Elastic Stack, our solutions, and software that supports our various deployment alternatives.

Because our solutions are built into the Elastic Stack, innovations and new capabilities in the Elastic Stack may benefit many of our solutions.

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

Technology Features of the Elastic Stack

Elasticsearch is the heart of the Elastic Stack, where users store, search, and analyze data.

Key features of Elasticsearch include the following:

Our platform consists of our three solutions (Elasticsearch, 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

Key features of our platform include the following:

• Storage of any type of data.

Elasticsearch combines powerful parts of traditional search engines, such as an inverted index to power fast full-text search and a column store for analytics, with native support for a wide range of data types, including text, dates, numbers, geospatial data, date/numeric ranges, and IP addresses.

With sensible defaults, and no upfront schema definition necessary, Elasticsearch makes it easy to start with simple storage solutions and fine-tune them as datasets grow.

• Vector search.

Elastic natively supports vector search as part of ESRE, which enables a wide range of advanced search use cases that improve relevance, including sophisticated search ranking, image search, question answering, and more.

Vector search relies on a next generation of machine learning models that can represent many types of content as vectors, including text, images, events, and more.

ESRE also supports integration with large language models.

As data volumes and formats proliferate, this sophisticated approach to search and relevance is becoming important for use cases where delivering maximum relevance is critical.

Our platform combines powerful parts of traditional search engines, such as an inverted index to power fast full-text search and a column store for analytics, with native support for a wide range of data types, including text, dates, numbers, geospatial data, date/numeric ranges, and IP addresses.

With sensible defaults, and no upfront schema definition necessary, our platform makes it easy to start with simple storage solutions and fine-tune them as datasets grow.

• Vector database.

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.

• Machine learning, AI, and alerting.

Machine learning capabilities such as anomaly detection, forecasting, and categorization are tightly integrated with the Elastic Stack 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.

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.

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Examples of these capabilities, all with a single search, include tracking the top ten users by expenditure level, looking at data week over week, analyzing data across geographies, and drilling down into details with specific filters.

• Developer friendliness.

• 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.

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Security features give administrators the rights to grant specific levels of access to their various types of users, such as IT, operations, and application teams.

Elasticsearch serves as the central authentication hub for the entire Elastic Stack.

Elasticsearch serves as the central authentication hub for our entire platform.

Security features include encrypted communications and encryption-at-rest;

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and audit logging.

Kibana is the user interface for the Elastic Stack.

It allows users to manage the Elastic Stack and visualize data.

Additionally, the interfaces for many of our solutions are built into Kibana.

Key features of Kibana include the following:

• Exploration and visualization of data stored in Elasticsearch.

Kibana provides interactive data views, visualizations, and dashboards powered by structured filtering and unstructured search to enable users to get to answers more quickly.

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.

Key features of our user interface include the following:

• Exploration and visualization of stored data.

Our platform’s user interface provides interactive data views, visualizations, and dashboards powered by structured filtering and unstructured search to enable users to get to answers more quickly.

Diverse user needs are supported by a variety of data visualization types, such as simple line and bar charts, purpose-built geospatial and time series visualizations, tree diagrams, network diagrams, heatmaps, scatter plots, and histograms.

• Incorporation of advanced analytics and machine learning from Elasticsearch.

Kibana’s query, filtering, and data summarization capabilities reflect Elasticsearch’s powerful query domain specific language and aggregation framework while making it interactive.

• Management of the Elastic Stack.

Kibana presents a broad user interface showing the health of Elastic Stack components and provides cluster alerts to notify administrators of problems.

Its central management user interfaces make it easier to operate the Elastic Stack at scale.

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.

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

Its central management user interfaces make it easier to operate our platform at scale.

• Home for solutions.

Kibana is where our users and customers access the user interfaces for our Search, Observability, and Security solutions.

Kibana provides core services, like security, alerting, and data visualization components.

This makes it easy for users to discover all of the capabilities our solutions provide and enables solution users to benefit from Kibana’s core capabilities.

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

Elasticsearch, 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.

• Application framework.

Kibana is designed to be extensible.

Users interested in a highly specialized visualization type not distributed with Kibana by default can customize experiences through a Kibana plugin and make the plugin available to the community.

Dozens of Kibana plugins have been shared by the community via Elastic documentation and code sharing platforms such as GitHub.

Elastic Agent, Beats, and Logstash are data ingestion tools that enable users to collect and enrich any kind of data from any source for storage in Elasticsearch.

Beats and Logstash have an extensible modular architecture.

Elastic Agent is a single, unified way to add monitoring for logs, metrics, and other types of data to each host, and also includes integrated host protection and central management.

Beats are lightweight agents purpose-built for collecting data on devices, servers, and inside containers.

Key features include the following:

• Data shippers.

Elastic Agent introduces a new single agent architecture across hosts that simplifies management and deployment.

Elastic Agent is based on the architecture of Beats, lightweight agents built for the purposes of efficient data collection at the edge for specific types of data, such as Filebeat for the collection of logging data, Metricbeat for the collection of system or service metric data, Auditbeat for the collection of security data, Packetbeat for the collection of network data, and Heartbeat for the collection of availability data.

Dozens of community Beats enable the collection of data from specialized sources.

• Extensibility and community Beats.

The Beats platform enables rapid creation of custom Beats that can be run on a variety of edge technologies for data collection.

Over 90 Beats have been shared by the community via Elastic documentation and many more are available through code sharing platforms such as GitHub.

• Host protection.

Specifically with Elastic Agent, we extend protection to hosts in addition to data transfer.

Elastic Agent stops malware and ransomware and enables environment-wide visibility and advanced threat detection.

Logstash enables centralized collection and extract, transformation, and load capabilities.

Key features of Logstash include the following:

• Data transformation engine.

Logstash is a centralized data transformation engine that can receive and pull data from multiple sources, transform and filter that data, and send it to multiple outputs.

Logstash has a powerful and flexible configuration language that allows users to create data stream acquisition and transformation logic without having to write code.

This capability greatly extends and accelerates the ability to create data management pipelines to a wide variety of organizations and individuals.

Logstash collects data from a variety of sources, such as network devices, queues, endpoints, and public cloud services.

Logstash enriches the data via lookups against local data sources, such as a geolocation database, and remote data sources, such as relational databases.

Logstash can output events to Elasticsearch or downstream queues and other data stores.

We develop and support more than 80 plugins for many common integrations.

• Logstash extensibility and community plugins.

A vibrant community of users extends our reach through hundreds of community Logstash plugins that enable integration with a wide variety of data sources across many use cases.

Our user interface is designed to be extensible.

Users interested in a highly specialized visualization type not distributed by default can customize experiences and make these customizations available to the community.

Dozens of customizations have been shared by the community via Elastic documentation and code sharing platforms such as GitHub.

Technology Features of our Solutions

Our solutions are designed to minimize time-to-value and deployment costs of using the Elastic Stack for common use cases.

Our solutions are designed to minimize time-to-value and deployment costs of using our platform for common use cases.

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.

Search gives users the tools to bring search experiences to customers, partners and teams quickly and scale them seamlessly.

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

• Search applications.

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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.

Observability combines analysis across the IT ecosystem of IT applications, networks, and infrastructure to deliver actionable insights into performance, availability, usability, adoption, and anomalous behavior.

Logs indexes, searches, and analyzes structured and unstructured logs at large scale to monitor the health and performance of an organization’s services, infrastructure, and applications.

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

• Log analytics.

Index, search, and analyze structured and unstructured logs at large scale to monitor the health and performance of an organization’s services, infrastructure, and applications.

Users can analyze and visualize information extracted from logs to understand system behavior and trends to optimize performance and preemptively address potential issues.

By querying logs in ad hoc ways, users can triage, troubleshoot, and resolve performance issues.

Metrics ingests, searches, visualizes, and analyzes numeric and time series data from IT systems, including applications, data stores, hosts, containers, cloud infrastructure, and more.

Users can review performance and utilization trends to optimize and plan for future needs.

Metrics helps users deliver on infrastructure service level objectives (“SLO”), and resolve downtime or performance issues by understanding how the state of individual components fits into the bigger picture.

Events allow users to monitor and respond to real-time operational happenings, ranging from security incidents to application-specific events.

By providing a chronological view of what is happening across their infrastructure, users can identify patterns or anomalies that could signify more significant issues.

Event data can also be correlated with logs and metrics to give a more comprehensive overview of system health and performance, facilitating faster root cause analysis and proactive management of operational risks.

APM delivers insight into application performance at the code level.

Developers can instrument apps and see the lifecycle of a transaction across services from front end to back end.

• Infrastructure monitoring.

With 400+ 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.

Users can instrument apps and see the lifecycle of a transaction across services from front end to back end.

This can give developers confidence in the code they ship, and can give operational teams visibility into code-level errors and performance bottlenecks to accelerate root cause analysis and resolution during an investigation.

• Synthetic Monitoring.

Customers and users leverage Synthetic Monitoring to track and monitor the availability of the hosts, websites, services, and application endpoints that support business operations.

Through proactive monitoring, customers can detect troublesome components before they are reported by end users.

Security delivers unified protection to prevent, detect, and respond to a variety of threats across the IT ecosystem.

Elastic SIEM automates threat detection and remediation, reducing mean time to detect (“MTTD”) and mean time to respond (“MTTR”).

With prebuilt Elastic Agent and Beats integrations, SIEM can ingest data from cloud, network, endpoints, applications, and other systems.

With Elastic Common Schema (“ECS”), users can centrally analyze information like logs, flows, and contextual data from disparate data sources.

SIEM provides an interactive workspace for security teams to detect and respond to threats.

Teams can triage events and perform investigations, gathering evidence on an interactive timeline.

SIEM also streamlines opening and updating cases, forwarding potential incidents to security operations workflows and IT ticketing systems.

• Digital experience monitoring.

Customers and users can identify problem areas and improve the overall experiences of their end users as they navigate their digital assets.

With synthetic monitoring, customers can track and monitor the availability of the hosts, websites, services, and application endpoints that support business operations.

Through proactive monitoring with synthetic monitoring and RUM, customers can detect troublesome components before they are reported by end users.

Always-on machine learning analysis instantly surfaces anomalies, patterns, correlations, and root causes.

AI Assistant and advanced machine learning enable interactive natural language chat experience that integrates with enterprise knowledge bases to quickly resolve issues.

• LLM observability.

LLM observability tracks costs, latency, errors, and dependencies of LLMs while ensuring safety and reliability.

Elastic Security delivers unified protection to prevent, detect, and respond to a variety of threats across the IT ecosystem.

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.

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

AI-assisted features help identify related alerts and prioritize what matters most.

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.

Endpoint Security combines prevention, detection, and response into a single, autonomous agent that can run even in isolated environments.

It is designed for ease of use and for speed, and can help stop threats in early stages of an attack.

Endpoint Security includes protection against ransomware, malware, phishing, exploits, fileless attacks, and other cybersecurity threats.

Extended Detection and Response (“XDR”) extends detection and response across the entire attack surface.

When deployed together, SIEM and Endpoint Security provide a strong security posture with broad visibility on potential threats.

XDR delivers a unified security stack, protecting across endpoints, cloud, and the broader environment, letting customers minimize vendor sprawl, harness actionable data, and provide defense in depth to minimize time to resolution.

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.

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

Prebuilt rules, machine learning jobs, and AI-driven analytics help detect multi-stage attacks that cross domains.

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

• Cloud security.

Cloud Security protects cloud deployments with rich visibility into cloud posture paired with runtime protection for cloud workloads with prevention, detection, and response capabilities, all in one integrated solution.

Our team extends beyond our employee base.

It includes all the users who download our software.

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.

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

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.

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

Each download of the Elastic Stack is a new opportunity to educate our next contributor, hear about a new use case, explore the need for a new feature, or meet a future member of the team.

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

Each download of our platform is a new opportunity to educate our next contributor, hear about a new use case, explore the need for a new feature, or meet a future member of the team.

Community is core to our identity, binding our products closely together with our users.

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Our principal competitors include:

• For Search and other platform use cases:

offerings such as Lucidworks Fusion and Apache Solr (open source offering), search tools including Algolia, Coveo, and Google.

• For Observability:

software vendors with specific observability solutions to analyze logging data, metrics, APM data, or infrastructure uptime, such as AppDynamics (owned by Cisco Systems), Datadog, Dynatrace, New Relic, and Splunk (owned by Cisco Systems).

• For Security:

security vendors such as Azure Sentinel (by Microsoft), Broadcom (which owns Carbon Black and Symantec), CrowdStrike, McAfee, and Splunk (owned by Cisco Systems).

• Certain cloud hosting providers and managed service providers, including AWS, that offer products or services based on a forked version of the Elastic Stack.

• 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 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).

• 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.

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

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• mindshare with developers and IT and security executives;

• adoption of products by many types of users and decision makers (developers, architects, DevOps personnel, IT professionals, security analysts, and departmental and organizational leaders);

• adoption of products by many types of users and decision makers (including developers, architects, DevOps personnel, IT professionals, security analysts, and departmental and organizational leaders);

• enterprise-grade technology that is secure and reliable;

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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, 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”).

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.

We obtain many components from software developed and released by contributors for independent open source components of our technology.

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We support both with human capital management efforts focused on:

• Attracting, engaging and retaining a talented and diverse employee base

• Maintaining our strong company culture

• Enhancing our commitment to diversity, equity, and inclusion (“DEI”)

• Attracting, engaging and retaining a talented employee base that values different perspectives, experiences, and backgrounds

• Facilitating strong employee engagement

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As of April 30, 2025, we had a total of 3,537 employees in over 40 countries globally.

Over 30% of our workforce consists of women and employees who self-identify as non-binary.

None of our U.S.

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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.

Our distributed model also expands our reach to a global candidate pool, broadening our ability to attract diverse talent across regions.

Diversity, Equity and Inclusion

Our focus on DEI is critical to how we develop, strengthen and sustain a sense of belonging and inclusion among all employees.

Balanced Teams.

We strive to be an employer of choice for a diverse and inclusive workforce through our talent brand, talent attraction, development, and retention efforts.

Our recruiting approach is underpinned by the desire to create balanced teams at Elastic, which includes considering broad aspects of diversity — not only race and gender, but also diversity of thought, experience and tenure.

We believe in empowering our employees to be their whole, creative selves and are proud to see this work recognized by Comparably, a workplace culture and compensation review platform, in nine major categories of its 2023 Best Place to Work series, including:

Best Company Culture, Best CEO for Diversity, and Best Company Work-Life Balance.

We also received an A+ culture score from Comparably.

Elastician Resource Groups.

We strive to embed DEI deep within our culture through various initiatives, projects, and programs, the centerpiece of which is our Elastician Resource Groups (“ERGs”), which are company-sponsored, self-organized, employee-run groups aligned with specific shared identities, interests, affinity or allyship.

Our seven ERGs encompass:

Accessibility, Black and African American, Asian and Pacific Islander+, Hispanic/Latinx, LGBTQIA+, Military/Veteran, and Women.

Fair Pay Practices.

Fair pay is the foundation of our compensation philosophy and the goal of fair pay informs our pay decisions around the globe.

This means paying people fairly for the job they perform without regard to gender, race, or ethnicity.

We partner with an external firm to conduct pay equity analysis on a regular basis using established job groupings and control factors to promote appropriate comparisons.

We look at gender globally and race and ethnicity for employees in the U.S.

Additionally, outside of the United States, we conduct supplemental country-specific analysis in accordance with local requirements.

Further recognizing that transparency is fundamental in fostering an equitable workplace where employees can trust that their compensation is based on fair and objective criteria, we provide all employees with information about the full salary range for their role.

Throughout the United States and Canada, we also include salary ranges on all job postings, in all states and provinces.

Code of Conduct .

To promote and reinforce our high standards of ethics and integrity throughout the entire company, we require all employees to acknowledge their compliance with our Code of Business Conduct and Ethics and complete mandatory training on this code, and on whistleblowing, anti-harassment, discrimination, anti-retaliation, and other key policies and standards.

Employee Engagement

Our distributed model also expands our reach, broadening our ability to attract talent across regions.

Culture and Values

At the core of our culture is our “Source Code”—a shared set of ideas that guide our approach to business with an emphasis on delivering value for our customers while providing flexibility and balance for our employees, empowering them to be their whole, creative selves.

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.

Through their collective experiences and feedback, our employees play a key role in enhancing our workplace environment.

We formally seek employee feedback through regular employee experience surveys.

We monitor employee morale and attitudes through two primary feedback mechanisms, consisting of – an annual employee engagement survey and a mid-year pulse survey check-in.

In fiscal 2024, our employees demonstrated high engagement with robust participation in the employee experience survey.

The results of these surveys are reviewed at the company, functional, team, and manager level, and are used to develop action plans.

Learning and Development

Elastic’s Learning & Organizational Development (L&OD) team’s vision is to enable purposeful growth for all employees by providing meaningful learning that can be applied in work and life.

Our L&OD team’s mission is to enable employees by providing the opportunity to pursue their purpose, in work and life.

To that end, we engage across a variety of mediums to ways in which we support the continuous learning and development of all Elasticians, including anytime access to on-demand video based learning and other opportunities.

We also conduct specific programs to develop managers and leaders at Elastic, including an externally-led leadership development program focused on high-performing leaders who possess the potential to have a significant strategic impact on the achievement of our long-term objectives.

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 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.

We deliver learning and development both through on-demand virtual learning and programs for specific teams or groups of emerging leaders.

Total Rewards

Compensation, Benefits and Well-being .

We aim to provide all employees with a total rewards package that is market-competitive, emphasizing global consistency and local relevance.

Compensation typically includes equity in the form of restricted stock units in addition to cash.

Reflecting our interest in the whole person, we provide benefit programs designed to enable employees to meet their well-being goals, from starting a family to being at their physical and emotional best.

These programs generally include core offerings of healthcare coverage and income protection plans, along with a focus on mental health and well-being.

We provide market-competitive paid time off programs, which feature 16 weeks of paid leave to all new parents, along with life-planning benefits.

In addition, we provide retirement savings plans, including a company-matched 401k plan for our U.S.-based employees.

Outside of the United States, we offer plans aligned to local market practice.

We also have adopted an employee stock purchase plan in which employees in countries are able to participate.

Flexible Work Environment .

As a distributed company, most employees have the flexibility to work anywhere provided that we have an established structure and it aligns with the needs of the business and their role.

We also recognize the importance of face-to-face interaction and maintain physical offices around the world to provide a space for employees to work and collaborate in a manner that fits their needs and preferences.

Community Involvement.

Through our Elastic Cares program, employees can support the charitable organizations that matter most to them on a local and global level.

We aim to provide all our employees with a total rewards package that is market-competitive, emphasizing global consistency and local relevance.

We are committed to fair pay without regard to gender, race, or ethnicity.

We partner with an external firm to conduct pay equity analysis on a regular basis using established job groupings and control factors to promote appropriate comparisons.

We provide benefit programs designed to enable employees to meet their well-being goals, from starting a family to being at their physical and emotional best.

Through our Elastic Cares program, our employees can support the charitable organizations that matter most to them on a local and global level.

This program encompasses donation matching, our nonprofit organization program which provides our technology for free to certain nonprofit organizations, and our volunteer time-off initiative.

Employees are encouraged to volunteer throughout the year with nonprofit organizations of their choosing using our volunteer time-off program, which provides our employees with 40 hours of paid volunteer time each year.

Employees who volunteer outside of their scheduled work day can also log their hours to earn donation credit which they can direct back to the cause of their choice.

Government Regulations

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Our compliance with existing or future governmental regulations, including, but not limited to, those pertaining to global trade, business acquisitions, consumer and data protection, and taxes, could have material impacts on our business.

See Item 1A, “Risk Factors” of this Annual Report on Form 10-K for a discussion of these potential impacts.

See Item “1A.

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

Corporate Information

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We announce material information to the public about us, our products and services, and other matters through a variety of means, including filings with the U.S.

Securities and Exchange Commission (“SEC”), press releases, public conference calls, our website (www.elastic.co), the investor relations section of our website (https://ir.elastic.co), our blog (www.elastic.co/blog), and/or social media, including our account on X (formerly known as Twitter) (https://x.com/elastic), our Facebook page (www.facebook.com/elastic.co), and/or LinkedIn account (www.linkedin.com/company/elastic-co), in order to achieve broad, non-exclusionary distribution of information to the public.

We encourage investors and others to review the information it makes public in these locations, as such information could be deemed to be material information.

Please note that this list may be updated from time to time.

We make available free of charge through our website our Annual Report on Form 10-K, Quarterly Reports on Form 10-Q, Current Reports on Form 8-K, and all amendments to these reports, as soon as reasonably practicable after we electronically file such materials with, or furnish them to, the SEC.

Securities and Exchange Commission (“SEC”), press releases, public conference calls, our website (www.elastic.co), the investor relations section of our website (https://ir.elastic.co), our blog (www.elastic.co/blog), and/or social media, including our account on X (https://x.com/elastic), our Facebook page (www.facebook.com/elastic.co), and/or LinkedIn account (www.linkedin.com/company/elastic-co) to achieve broad, non-exclusionary distribution of information to the public.

We encourage investors and others to review the information we make public in these locations, as such information could be deemed to be material information.

This list may be updated from time to time.

We make available, free of charge through our website, our Annual Report on Form 10-K, Quarterly Reports on Form 10-Q, Current Reports on Form 8-K, and all amendments to these reports as soon as reasonably practicable after we electronically file such material with, or furnish it to, the SEC.

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