Definition
A technique that connects an AI model to the company's documents: the AI retrieves the relevant passages before answering, with cited sources.
RAG (Retrieval-Augmented Generation) solves the main limitation of LLMs: they don't know your internal data. The principle: your documents (contracts, procedures, wikis, emails) are indexed in a vector database; for each question, the system retrieves the most relevant passages and provides them to the model, which answers while citing its sources.
RAG sharply reduces hallucinations and makes AI genuinely useful in the enterprise. Sovereign point of attention: the index contains a condensed copy of your most sensitive documents, it must be hosted within your perimeter, not in a third party's cloud.
All AI models, deployed on your infrastructure, with your documents connected.