How does agentic AI work?

Agentic AI operates through a continuous sense–think–act loop — often described as perceive → reason → plan → act.

Perceive — Agents collect live signals from sensors, APIs, and event streams.
Reason — LLMs and domain logic interpret inputs and infer next steps.
Plan — Agents decompose goals, select actions, and sequence tools.
Act — They execute API calls, publish events, and update systems — generating new data that restarts the loop.

When many agents share context through an event mesh, they form a living ecosystem of intelligence that learns and reacts continuously.

To make AI agents work in production, enterprises needs a new architecture—one built on real-time data, governance, and event-driven orchestration.

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Our Chief Engineering Officer explains why EDA is the perfect fit for the asynchronous workloads of generative AI.

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Our Chief AI Officer breaks down the way EDA brings AI to life, and how AI adds intelligence to your data distribution.

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This post breaks down explains how EDA can help you use LLMs and RAG to build smarter applications that work with live, real-time data.

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This post breaks down explains how EDA can help you use LLMs and RAG to build smarter applications that work with live, real-time data.

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SAM Enterprise Edition leverages the vendor's event messaging and governance capabilities, integrating agents with enterprise systems and...

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