TL;DR
An agentic RAG pipeline treats retrieval as a tool the AI agent can call, evaluate, and call again rather than as a fixed step.
The pipeline can search an internal knowledge base first, then use real-time web search when the available evidence is missing, weak, or outdated.
Internal documents and web results should be converted into a shared evidence format before the model generates an answer.
A reliable system must preserve URLs, publication dates, document identifiers, and the claims supported by each source.
