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Glossary·
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RAG (retrieval-augmented generation)
A technique where a language model is given relevant excerpts from your own documents at the moment of answering, instead of relying only on what it learned during training.
Why it matters
It is how an assistant answers about your prices, policies, and documentation without inventing them, and how answers stay current: updating the source document is enough, no retraining is involved.
How we approach it
We build the retrieval layer carefully — chunking, embeddings, filters, ranking — require the model to cite the source passage, and make it answer that it does not know when nothing relevant is found.
