Powering the world's most sophisticated AI search and RAG applications with the Elasticsearch Relevance Engine.
Elastic AI, built upon the Elasticsearch Relevance Engine (ESRE), represents the 2026 pinnacle of retrieval-augmented generation (RAG) and semantic search technology. It integrates a distributed vector database with advanced relevance ranking, allowing developers to build AI applications that are grounded in private, real-time data. The architecture provides a unified platform for dense vector search, sparse vector search (ELSER), and traditional keyword search (BM25), enabling 'hybrid search' that outperforms single-method systems. By 2026, Elastic has solidified its position as the critical infrastructure for LLM-powered applications, offering built-in inference APIs that connect seamlessly to providers like OpenAI, Azure AI, and Hugging Face. The platform excels in handling petabyte-scale datasets while maintaining sub-second latency, a requirement for modern generative AI agents. Its technical maturity allows for sophisticated data chunking, automated embedding generation, and complex permission-based filtering at the search layer, ensuring that AI responses are not only accurate but also compliant with enterprise security standards.
An out-of-the-box sparse vector model designed for high-recall semantic search without the need for custom training.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
A scoring algorithm that combines results from different search methods (keyword + vector) into a single ranked list.
A unified interface to call external LLMs or internal ML models during the ingestion or search pipeline.
Implementation of Hierarchical Navigable Small World graphs for efficient approximate nearest neighbor search.
Allows searching directly against data stored in S3 or Object Storage while maintaining low costs.
Advanced filtering that ensures users only retrieve search results (and RAG context) they are authorized to see.
The ability to perform a single AI-driven search across multiple clusters and geographic regions.
LLMs hallucinating or providing outdated answers to technical queries.
Registry Updated:2/7/2026
Return the grounded response to the customer.
Users struggle to find items using keywords only.
Identifying complex fraudulent patterns in high-velocity transaction streams.