Powering the generative AI era

Elasticsearch can cost-effectively and securely link your proprietary data with large language models (LLMs) for application output that’s up-to-date, accurate, relevant, and business specific. Use the power of Elasticsearch and its vector database with your own transformer models or integrate with generative AI to build new customer and employee experiences.

Video thumbnail

Benefit from a relevance engine tailor-made for developers who build AI powered search applications.

Read Elasticsearch Relevance Engine blog

Learn about Elastic AI Assistant, our first domain-specific application of generative AI.

Read announcement

Hear Elastic's CPO, Ken Exner, discuss Elastic’s pivotal role in AI acceleration.

Watch video

How It Works

Look inside the context window

Elastic uses retrieval augmented generation (RAG) to present generative AI with relevant search results from your data.

When an end-user makes a query, Elastic searches your data stored in Elasticsearch to generate relevant search results. Then, it passes this context along to the generative AI model, which combines its knowledge with context from your business data in its response to the user.

Built with AI in Mind

With new technology, comes enhanced tools

The Elasticsearch Relevance Engine™ gives developers a full suite of sophisticated retrieval algorithms for building AI apps and the ability to integrate with large language models (LLMs). Highly scalable and built on a proven, production-ready tech stack.

  • Vector database

    Download, select your components, and add a few lines of code to your application.

  • Elastic Learned Sparse Encoder

    Elastic's ML model delivers highly relevant semantic search out-of-the-box, without domain adaptation. It's available with one click while configuring your search application. It expands queries with related keywords and relevance scores, so they're easily interpretable and ready for use right away.

  • Large language models

    Give LLMs business-specific information using your private data (not just publicly trained data). Use Elasticsearch for high relevance context windows that draw on your proprietary data to improve LLM output and relevance. Access generative AI with APIs and plugins integrated with the LLM of your choice.

Dive In

Ready to get started?

Set up a free trial or learn more about Elastic's easy to implement semantic search model and use cases for using Elastic to build search apps with generative AI.

  • Start free trial

    Spin up a free 14-day Elastic Cloud to start exploring how to use Elasticsearch with generative AI.

  • Learn how to use Elastic Cloud to easily set up semantic search in a few short steps.

  • Create AI apps

    Build next-gen apps for personalized responses, question-answering, and real-time data insights.

Learn how to use ChatGPT with Elasticsearch

Discover how to combine Elasticsearch's search relevance with OpenAI's ChatGPT question-answering to query your private data.

Read blog