IMPORTANT: No additional bug fixes or documentation updates
will be released for this version. For the latest information, see the
current release documentation.
Beyond full-text search
The Elasticsearch Relevance Engine (ESRE) is a collection of relevance tools for developing advanced search applications using machine learning (ML) and artificial intelligence (AI).
Expand your usage of Elasticsearch by combining keyword matching with semantic search and integrations with generative AI. Provide search results based on contextual meaning and user intent, or display generated answers and other relevant content in response to user input.
Learn more about the Elastic features that compose ESRE, view example applications and notebooks, or get help with your specific application.
More ESRE content from Elastic
- Elasticsearch Relevance Engine (product page)
- Generative AI (blog category)
- Enhancing chatbot capabilities with NLP and vector search in Elasticsearch
- ChatGPT and Elasticsearch: Faceting, filtering, and more context
- Superior relevance with Elastic Learned Sparse Encoder and hybrid scoring
- Elastic Enterprise Search 8.8: Easy AI-powered search for your enterprise
- The power of generative AI for public sector
- Introducing Elasticsearch Relevance Engine™ — Advanced search for the AI revolution
- Improving information retrieval in the Elastic Stack: Introducing Elastic Learned Sparse Encoder, our new retrieval model
- Introducing Elastic Learned Sparse Encoder: Elastic’s AI model for semantic search
- Accessing machine learning models in Elastic
- Privacy-first AI search using LangChain and Elasticsearch
- How to use Elasticsearch to prompt ChatGPT with natural language
- ChatGPT and Elasticsearch: A plugin to use ChatGPT with your Elastic data
- The impact of absolute values vs. percentages on effective machine learning
- ChatGPT and Elasticsearch: OpenAI meets private data