A retrieval-augmented generation pipeline where software automatically evaluates initial search results and executes follow-up database queries if needed.

A top-tier 2020s buzzword that combines "agentic" with Retrieval-Augmented Generation (RAG). It creates the illusion of an intrepid research scholar digging through dusty library archives, when in reality it's a script running a second database search pass if the first query returned low similarity scores.

• Intrepid Scholar Roleplay: Treating a multi-pass database vector lookup like an adventurous academic expedition.
• Double Acronym Density: Stacking trendy AI acronyms together to confuse corporate buyers into paying higher license fees.
• Query Latency Overhead: Running multiple automated database search passes that slow down response times for simple questions.

Matlock (1980s) S1 scene where Ben Matlock sits at his cluttered wooden desk in his rumpled grey suit, eating a hot dog while meticulously flipping through thick legal volumes to find an obscure state statute that proves his client's innocence.

A document search tool that automatically re-runs database queries with refined terms if initial results are unhelpful.

“Our agentic RAG pipeline ensures model responses are grounded in verified enterprise documents.”

“Our search tool automatically tries a broader database search if its initial document search comes up empty.”