Retrieval-Augmented Generation (RAG)

An architecture where a generative model is conditioned on external retrieved documents, typically via vector search, to produce grounded, context-aware outputs.

Why this matters:

If the retrieval layer omits or misranks corporate data, LLMs will answer using third-party sources, creating revenue leakage and brand misrepresentation.