What is Agentic RAG?
TL;DR
An advanced RAG approach that combines retrieval with autonomous AI agent decision-making for multi-step information gathering.
Agentic RAG: Definition & Explanation
Agentic RAG is an advanced approach that combines traditional RAG (Retrieval-Augmented Generation) with the autonomous decision-making capabilities of AI agents. While conventional RAG follows a simple single-step retrieve-then-generate pipeline, Agentic RAG has the AI agent autonomously decide 'which information sources to search,' 'whether additional searches are needed,' and 'whether the information is reliable enough.' It performs multi-step information gathering, verification, and synthesis. Specific capabilities include query decomposition (breaking complex questions into smaller sub-queries), source selection (choosing the optimal source from internal databases, web search, APIs, etc.), iterative retrieval (evaluating initial results and performing follow-up searches if gaps are found), and information synthesis and validation (integrating information from multiple sources and checking for contradictions). In 2026, Agentic RAG is rapidly replacing traditional RAG as the dominant architecture in enterprise AI.