Microsoft and Elastic are thrilled to announce that Elasticsearch, the world's most downloaded vector database is an officially supported vector store and retrieval augmented search technology for Azure OpenAI Service On Your Data in public preview. The groundbreaking feature empowers you to leverage the power of OpenAI models, such as GPT-4, and incorporates the advanced capabilities of RAG (Retrieval Augmented Generation) model, directly on your data with enterprise-grade security on Azure. Read the announcement from Microsoft here.
Azure OpenAI Service On Your Data makes conversational experiences come alive for your employees, customers and users. With the addition of Elasticsearch vector database and vector search technology, LLMs are enriched by your business data, and conversations deliver superior quality responses out-of-the-box. All of this adds up to helping you better understand your data, and make more informed decisions.
Build powerful conversational chat experiences, fast
Business users, such as users on e-commerce teams, product managers, and others can add documents from an Elasticsearch index to build a conversational chat experience very quickly. All it takes is a few simple steps to configure the chat experience with parameters such as message history, and you're good to go! Customers can realize benefits pretty much right away..
- Quickly roll out conversational experiences to your users, customers, or employees--backed by context from your business data
- Common use cases include offering internal knowledge search, users self-service, or chatbots that help process common business workflows

How Elasticsearch vector database works with On Your Data
The new native experience within Azure OpenAI Studio makes adding an Elastic index a simple matter. Developers can pick Elasticsearch as their chosen vector database option from the drop-down menu..

You can bring your existing Elasticsearch indexes to On Your Data—whether those indexes live on Azure or on-prem. Just select Elasticsearch as your data source, add your Elastic endpoint and API key, add an Elastic index, and you're all set!

With the Elasticsearch vector database running in the background, users get all the Elastic advantages you'd expect.
- Precision of BM25 (text) search, the semantic understanding of vector search, and the best of both worlds with hybrid search
- Document and field level security, so users can only access information they're entitled to based on their permissions
- Filters, facets, and aggregations that add a real boost to how quickly relevant context is pulled from your organisation's data, and sent to an LLM
- Choice of leveraging a range of large language model providers, including Azure OpenAI, Hugging Face, or other 3rd party models
Elastic on Microsoft Azure: a proven combination
Elastic is a proud winner of the Worldwide Microsoft Partner of the Year award for Commercial Marketplace. Elastic and Microsoft customers have been using Elasticsearch and Azure OpenAI to build futuristic search experiences, that leverage the best of AI and machine learning, today.
Ali Dalloul, VP, Azure AI Customer eXperience Engineering had this to say about the collaboration, "By harnessing the power of Azure Cloud and OpenAI, Elastic is driving the development of AI-driven solutions that redefine customer experiences. This partnership is more than just a collaboration; it's a feedback loop of innovation, benefiting customers, Elastic, and Microsoft, while empowering the broader partner ecosystem. We're delighted to offer customers Elasticsearch's strong vector database and retrieval augmentation capabilities to store and search vector embeddings for On Your Data."
"This really helps customers connect data wherever it lives. We are happy to open the spectrum of building conversational AI solutions, agnostic to location, including Elasticsearch. We are excited to see how developers build upon this integration." Adds Pavan Li, Principal Product Manager of Azure OpenAI Service On Your Data.
Elastic's clear strengths in hybrid search--combining BM25/text search with vector search for semantic relevance, was an important differentiator. With the backing of the open source Apache Lucene community, Elastic's vector database has already been widely adopted by large companies for enterprise scale use cases.
Try On Your Data with Elasticsearch vector database today
Unlock the insights with conversational AI, using Elasticsearch and Azure OpenAI On Your Data today!
- Visit Azure OpenAI Studio to build your first conversational copilot
- Connect Elasticsearch with OpenAI models
- Read more on the Microsoft Tech Community blog
Ready to try this out on your own? Start a free trial.
Want to get Elastic certified? Find out when the next Elasticsearch Engineer training is running!
Related content

March 13, 2026
Entity resolution with Elasticsearch, part 4: The ultimate challenge
Solving and evaluating entity resolution challenges in a highly diverse “ultimate challenge” dataset designed to prevent shortcuts.

March 4, 2026
Entity resolution with Elasticsearch, part 3: Optimizing LLM integration with function calling
Learn how function calling enhances LLM integration, enabling a reliable and cost-efficient entity resolution pipeline in Elasticsearch.

February 26, 2026
Entity resolution with Elasticsearch & LLMs, Part 2: Matching entities with LLM judgment and semantic search
Using semantic search and transparent LLM judgment for entity resolution in Elasticsearch.

February 18, 2026
Better text analysis for complex languages with Elasticsearch and neural models
Using neural models and the Elasticsearch inference API to improve search in Hebrew, German, Arabic, and other morphologically complex languages.

February 12, 2026
Entity resolution with Elasticsearch & LLMs, Part 1: Preparing for intelligent entity matching
Learn what entity resolution is and how to prepare both sides of the entity resolution equation: your watch list and the articles you want to search.