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RAG

Retrieval-augmented generation finds relevant passages in a knowledge base before a language model answers. It helps ground replies in company information, while still requiring source and accuracy checks.

What happens before the answer

The system retrieves relevant document passages and supplies them to a language model with the question. Company information can then be updated without retraining the model for every price change.

What determines accuracy

Source quality, retrieval, access controls and answer evaluation all matter. RAG reduces unsupported answers but cannot eliminate them. Source links and human handoff are useful safeguards.

When it is appropriate

It helps with many documents and varied question wording. For a small knowledge base, ordinary search and prepared replies may be enough. We compare quality and cost before selecting an approach.

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