Blogs
Developer insights and practical how-to articles from our experts to inspire and empower your search experience.
Fast vs. accurate: Measuring the recall of quantized vector search
Explaining how to measure recall for vector search in Elasticsearch with minimal setup.
Testing Elasticsearch. It just got simpler.
Explaining how Elasticsearch integration tests have become simpler thanks to improvements in Elasticsearch 9.x, the modern Java client, and Testcontainers 2.x.
AI agent memory: Creating smart agents with Elasticsearch managed memory
Learn how to create smarter and more efficient AI agents by managing memory using Elasticsearch.
The Gemini CLI extension for Elasticsearch with tools and skills
Introducing Elastic’s extension for Google's Gemini CLI to search, retrieve, and analyze Elasticsearch data in developer and agentic workflows.
Agent Skills for Elastic: Turn your AI agent into an Elastic expert
Give your AI coding agent the knowledge to query, visualize, secure, and automate with Elastic Agent Skills.
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.
The stateless architecture of Elasticsearch Serverless
Exploring the stateless architecture of Elasticsearch Serverless. Learn how the stateful architecture was transformed into stateless for Serverless.
Hybrid search with Java: LangChain4j Elasticsearch integration
Learn how to use hybrid search in LangChain4j via its Elasticsearch integrations, with a complete Java example.
SearchClaw: Bring Elasticsearch to OpenClaw with composable skills
Give your local AI agent access to Elasticsearch data using OpenClaw, composable skills, and agents, no custom code required.
Building effective database retrieval tools for context engineering
Best practices for writing database retrieval tools for context engineering. Learn how to design and evaluate agent tools for interacting with Elasticsearch data.
Build task-aware agents with an expanded model catalog on Elastic Inference Service (EIS)
Elastic Inference Service (EIS) expands its managed model catalog, enabling teams to build production-ready agents with flexible model choice across retrieval, generation, and reasoning, without managing GPUs or infrastructure.
