glossary
RAG is a method where a language model retrieves relevant documents and grounds its answer in them.
RAG lets the model answer from your up-to-date knowledge base rather than only its training, improving accuracy and enabling source citations.
Examples
Retrieving the relevant policy doc to answer a policy question.
It reduces hallucination and grounds answers in verifiable sources.
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