Hybrid Search

AI shopping agents: Why context comes before the query

AI shopping agents that guess at your vocabulary make expensive mistakes. Pre-computed catalog context stops the guessing before the first tool call.

AI shopping agents: Why context comes before the query
jina-clip-v2 brings text-to-image search across 89 languages to Elasticsearch, no GPU needed

June 23, 2026

jina-clip-v2 brings text-to-image search across 89 languages to Elasticsearch, no GPU needed

Run multimodal search across 89 languages inside Elasticsearch with jina-clip-v2: one embedding space for text and images, with no separate model infrastructure to manage.

How we built a persistent agent memory layer on Elasticsearch with 0.89 recall and zero tenant leaks

How we built a persistent agent memory layer on Elasticsearch with 0.89 recall and zero tenant leaks

Discover the architecture behind a persistent, multi-tenant agent memory layer on Elasticsearch: three indices, hybrid retrieval with RRF and a reranker, supersession, decay, and per-user DLS isolation. R@10 0.89 across 168 questions. Full open-source implementation included.

Best practices for building a modern app with vector search

Best practices for building a modern app with vector search

Exploring six vector search tips for building modern AI search applications entirely on Elasticsearch, with an opinionated rationale at each architectural decision.

Cutting agent costs with pre-computed context

Cutting agent costs with pre-computed context

Pre-computing context as Knowledge Indicators reduces LLM agent token costs by up to 75% and improves answer accuracy from 60% to 92%. This post covers the extraction, retrieval and feedback loop that make it work, tested against the BrowseComp-Plus benchmark.

How to measure and improve Elasticsearch search recall: from 0.43 to 0.75 with hybrid search

How to measure and improve Elasticsearch search recall: from 0.43 to 0.75 with hybrid search

Learn how to measure and improve search recall in Elasticsearch by combining BM25 lexical search with Jina AI vector embeddings, using the rank_eval API to validate the improvement with real numbers.

Entity resolution with Elasticsearch, part 4: The ultimate challenge

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.

Hybrid search with Java: LangChain4j Elasticsearch integration

Hybrid search with Java: LangChain4j Elasticsearch integration

Learn how to use hybrid search in LangChain4j via its Elasticsearch integrations, with a complete Java example.

Entity resolution with Elasticsearch, part 3: Optimizing LLM integration with function calling

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.

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