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Elastic Announces General Availability of Agent Builder with Expanded Capabilities

Elastic Agent Builder grounds AI agents in enterprise data, executes context-driven answers and actions

Elastic announced the general availability of Agent Builder, a complete set of capabilities that helps developers quickly build secure, reliable, context-driven AI agents.

AI agents need the right context to perform complex tasks accurately. Built on Elasticsearch, Agent Builder excels at context engineering by delivering relevance in a unified platform that scales, searches, and analyzes enterprise data. It dramatically simplifies the entire agent workflow with native data prep and ingestion, retrieval and ranking, built-in and custom tools, native conversational experience, and agent observability. Developers can use Agent Builder to chat with their data or build a context-driven custom agent in minutes.

"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."

"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."

“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.”

Introducing Workflows

Elastic also introduced Elastic Workflows (tech preview), a new capability that extends Agent Builder’s functionality by enabling agents to reliably take action across systems.

Many agent-building frameworks require LLMs to plan and manage every step of the automation. However, AI lacks the reliability of rule-based actions, a critical capability for organizations. Workflows closes this gap. Now, agents built with Agent Builder can leverage Workflows to orchestrate internal and external systems to take actions, gather and transform data and context with precision. Agent Builder and Workflows enable developers to build context-driven agents that can reason accurately and execute predictably.

"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.”

Agents developed with Agent Builder are model-agnostic and compatible with managed model-as-a-service providers, including the cloud hyperscalers.

Availability

Agent Builder is available in Elastic Cloud Serverless and is included with the Enterprise Tier in Elastic Cloud Hosted and self-managed Elastic Stack releases for existing customers.

Workflows is available in tech preview.

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Elastic Announces General Availability of Agent Builder with Expanded Capabilities

Elastic Agent Builder grounds AI agents in enterprise data, executes context-driven answers and actions

Elastic announced the general availability of Agent Builder, a complete set of capabilities that helps developers quickly build secure, reliable, context-driven AI agents.

AI agents need the right context to perform complex tasks accurately. Built on Elasticsearch, Agent Builder excels at context engineering by delivering relevance in a unified platform that scales, searches, and analyzes enterprise data. It dramatically simplifies the entire agent workflow with native data prep and ingestion, retrieval and ranking, built-in and custom tools, native conversational experience, and agent observability. Developers can use Agent Builder to chat with their data or build a context-driven custom agent in minutes.

"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."

"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."

“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.”

Introducing Workflows

Elastic also introduced Elastic Workflows (tech preview), a new capability that extends Agent Builder’s functionality by enabling agents to reliably take action across systems.

Many agent-building frameworks require LLMs to plan and manage every step of the automation. However, AI lacks the reliability of rule-based actions, a critical capability for organizations. Workflows closes this gap. Now, agents built with Agent Builder can leverage Workflows to orchestrate internal and external systems to take actions, gather and transform data and context with precision. Agent Builder and Workflows enable developers to build context-driven agents that can reason accurately and execute predictably.

"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.”

Agents developed with Agent Builder are model-agnostic and compatible with managed model-as-a-service providers, including the cloud hyperscalers.

Availability

Agent Builder is available in Elastic Cloud Serverless and is included with the Enterprise Tier in Elastic Cloud Hosted and self-managed Elastic Stack releases for existing customers.

Workflows is available in tech preview.

The Latest

The gap is widening between what teams spend on observability tools and the value they receive amid surging data volumes and budget pressures, according to The Breaking Point for Observability Leaders, a report from Imply ...

Seamless shopping is a basic demand of today's boundaryless consumer — one with little patience for friction, limited tolerance for disconnected experiences and minimal hesitation in switching brands. Customers expect intuitive, highly personalized experiences and the ability to move effortlessly across physical and digital channels within the same journey. Failure to deliver can cost dearly ...

If your best engineers spend their days sorting tickets and resetting access, you are wasting talent. New global data shows that employees in the IT sector rank among the least motivated across industries. They're under a lot of pressure from many angles. Pressure to upskill and uncertainty around what agentic AI means for job security is creating anxiety. Meanwhile, these roles often function like an on-call job and require many repetitive tasks ...

In a 2026 survey conducted by Liquibase, the research found that 96.5% of organizations reported at least one AI or LLM interaction with their production databases, often through analytics and reporting, training pipelines, internal copilots, and AI generated SQL. Only a small fraction reported no interaction at all. That means the database is no longer a downstream system that AI "might" reach later. AI is already there ...

In many organizations, IT still operates as a reactive service provider. Systems are managed through fragmented tools, teams focus heavily on operational metrics, and business leaders often see IT as a necessary cost center rather than a strategic partner. Even well-run ITIL environments can struggle to bridge the gap between operational excellence and business impact. This is where the concept of ITIL+ comes in ...

UK IT leaders are reaching a critical inflection point in how they manage observability, according to research from LogicMonitor. As infrastructure complexity grows and AI adoption accelerates, fragmented monitoring environments are driving organizations to rethink their operational strategies and consolidate tools ...

For years, many infrastructure teams treated the edge as a deployment variation. It was seen as the same cloud model, only stretched outward: more devices, more gateways, more locations and a little more latency. That assumption is proving costly. The edge is not just another place to run workloads. It is a fundamentally different operating condition ...

AI can't fix broken data. CIOs who modernize revenue data governance unlock predictable growth-those who don't risk millions in failed AI investments. For decades, CIOs kept the lights on. Revenue was someone else's problem, owned by sales, led by the CRO, measured by finance. Those days are behind us ...

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Ask where enterprise AI is making its most decisive impact, and the answer might surprise you: not marketing, not finance, not customer experience. It's IT. Across three years of industry research conducted by Digitate, one constant holds true is that IT is both the testing ground and the proving ground for enterprise AI. Last year, that position only strengthened ...