Artificial Intelligence

Retrieval-Augmented Generation

Acronym : RAG

RAG combines a document retrieval engine with an LLM: before answering, the system fetches the most relevant passages from a company's own knowledge base, then feeds them into the model's context.

Why it matters

RAG lets an AI answer using a company's own up-to-date information without retraining the model, while significantly reducing the risk of hallucination.

Concrete example

Kaliteq's Smart Hub uses RAG to answer team questions by relying on the documents uploaded to the diagnostic's Data Room.

Related notions

Knowledge baseVector searchAugmented context

Go further

Smart Hub and RAG: turning your audits into a knowledge base

Related Kaliteq diagnostics

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Assesses AI governance and usage, inspired by ISO/IEC 42001, the NIST AI RMF and the EU AI Act.

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