Elastic released Agent Builder, a complete set of capabilities powered by Elasticsearch, that makes it easy for developers to build custom AI agents on company data—all within minutes.
Agent Builder also provides an out-of-the-box conversational experience for exploring, analyzing, and optimizing any data in Elasticsearch.
As AI agents evolve to take on more complex and data-driven enterprise tasks, reliability and accuracy depend on delivering accurate context. In most enterprises, this context is scattered across various unstructured data sources, including documents, emails, business apps, and customer feedback. The process for getting the relevant context into agents at the right time is known as context engineering.
While Elasticsearch has always been a platform for the core of context engineering, Agent Builder expands on this strength. It simplifies the entire operational lifecycle of agents, their development, configuration, execution, customization, and observability directly into Elasticsearch.
”AI agents don’t just need lots of data, they need the right data and tools, with relevance, guardrails, and observability built in,” said Ken Exner, chief product officer at Elastic. “Developers already rely on Elasticsearch to find the right answer from their messy business data. Agent Builder goes further by making Elasticsearch one of the fastest platforms to build precise AI agents that use your data, where retrieval, governance, and orchestration all operate in one place, natively.”
With Agent Builder, developers have built-in tools that go beyond basic run queries of open-standard Model Context Protocol (MCP) endpoints. Users of Agent Builder on Elasticsearch can ask natural language questions, identify which indexes to query, configure searches, define agent parameters and more.
With Agent Builder, developers can:
