FAQ as RAG: When You Get to Design the Corpus

Using a well-structured FAQ as a corpus for a Retrieval-Augmented Generation (RAG) system inverts and simplifies the typical pipeline. Since the corpus is authored and not inherited, parsing becomes a simple task of loading a structured file with a predefined schema. The retrieval step functions as a cache, classifying user queries as direct matches, adjacent matches, or misses based on similarity to canonical questions. Direct matches return pre-written answers instantly without an LLM call, while adjacent matches use the retrieved FAQ entries as few-shot examples for a tailored response, and misses highlight content gaps for editorial review.