Elastic, widely known as the Search AI Company, has officially announced the general availability of Agent Builder, a comprehensive solution designed to help developers quickly create secure, reliable, and context-aware AI agents. With enterprises increasingly relying on AI to handle complex workflows, Elastic positions Agent Builder as a powerful platform that simplifies how agents access, understand, and act on data.
To begin with, AI agents depend heavily on accurate and relevant context to deliver meaningful outcomes. Addressing this need, Elastic built Agent Builder on top of Elasticsearch, enabling advanced context engineering at scale. As a result, developers gain access to a unified platform capable of searching, analyzing, and scaling enterprise data while ensuring high relevance. Moreover, the solution streamlines the entire agent lifecycle by combining native data preparation and ingestion, advanced retrieval and ranking, built-in and custom tools, a conversational interface, and full agent observability. This integrated approach allows developers to either chat directly with their data or deploy a custom, context-driven agent within minutes.
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Notably, Elastic has strengthened interoperability by enabling native support for modern AI protocols. “Agent Builder has native MCP and A2A protocol support, enabling seamless deployments within Microsoft Foundry and Microsoft Agent Framework,” said Amanda Silver, CVP, Microsoft CoreAI. “This gives our users a way to build context-rich, agentic AI leveraging Elasticsearch as a Knowledge Source and powered by Microsoft Foundry.” This integration highlights Elastic’s commitment to fitting naturally into existing enterprise AI ecosystems.
At the same time, Elastic is addressing one of the biggest challenges in agentic AI: complexity. “Agentic systems fail today because connecting AI to tools and data is complex,” said Sam Partee, co-founder at Arcade.dev. “Elastic Agent Builder with Arcade.dev gives developers a structured, secure way to handle how agents retrieve context, reason, and act, taking agents from demo to production grade.” By simplifying these connections, Agent Builder helps organizations move beyond experimental prototypes.
In addition, Elastic is enhancing how agents process unstructured enterprise data. “Unlocking enterprise context from unstructured data sources is key to building effective agents,” said Jerry Liu, CEO at LlamaIndex. “Elastic Agent Builder combined with LlamaIndex’s complex document processing strengthens the critical context layer, helping teams retrieve, process, and prepare data so agents can reason more accurately and deliver better outcomes.” This collaboration ensures agents can reason with higher accuracy and deliver consistent value.
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Alongside Agent Builder, Elastic introduced Elastic Workflows in tech preview. This new capability extends agent functionality by enabling predictable, rules-based automation across internal and external systems. Unlike traditional frameworks that rely on large language models to plan every step, Workflows adds reliability by combining intelligent reasoning with deterministic execution. Consequently, agents can orchestrate actions, transform data, and manage workflows with precision.
Summing up the vision, “Agent Builder simplifies working with messy enterprise data, giving developers a secure, reliable foundation to build context-driven agents at scale,” said Ken Exner, chief product officer at Elastic. “Elastic Workflows complements this foundation by giving those agents built-in, rules-based automation for simple tasks. By enhancing Agent Builder with Workflows, teams get a single system that delivers both intelligent reasoning and dependable automation, which is exactly what enterprises need to move from pilots to real-world impact.”
Importantly, agents built with Elastic Agent Builder remain model-agnostic and work seamlessly with managed model-as-a-service providers, including major cloud hyperscalers. This flexibility ensures enterprises can future-proof their AI strategies while scaling intelligent agents confidently across real-world use cases.
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