RAG (Retrieval-Augmented Generation)
Definition
RAG is a technique where a language model retrieves relevant documents from a private knowledge base and uses them as context, so answers are grounded in the organisation's own verified information.
Without retrieval, a model answers from training data and will fabricate specifics it does not know. RAG constrains it to source material the business controls — product documentation, policies, past campaigns — which makes outputs both accurate and citable.
It is the right architecture for internal knowledge assistants and customer support agents. Quality depends far more on how the source documents are chunked, indexed and kept current than on which model sits on top.
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A short call, then a written review inside 72 hours: what your marketing costs, what it produces, and what is worth fixing first.