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.
Benefit from a relevance engine tailor-made for developers who build AI powered search applications.
Read Elasticsearch Relevance Engine blogLearn about Elastic AI Assistant, our first domain-specific application of generative AI.
Read announcementHear Elastic's CPO, Ken Exner, discuss Elastic’s pivotal role in AI acceleration.
Watch videoHow 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.
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.
Set up semantic search
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.
UNLOCK GENERATIVE AI
Your data is the key
Use Elastic to develop generative AI experiences that tap into your domain-specific proprietary data. Make the most of your real-time data for increased efficiency and process automation, improved customer experience, and a competitive advantage.
What is generative AI