RAG (Retrieval-Augmented Generation)

Data & retrieval

RAG combines information retrieval and text generation: before answering, the AI fetches the relevant passages from a dedicated document base (reports, contracts, FAQs…), then generates its answer from those sources. It is the most reliable way to get precise, contextualised answers grounded in company data rather than in the model's memory alone.

In practice at Gensai

RAG sits at the heart of Gensai's answer engines and chatbots, including the compliance assistant on a sovereign RAG and the Oceans voice installation.

Same theme

Vector database Reranking Embedding Semantic search

RAG (Retrieval-Augmented Generation)

In practice at Gensai

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In application

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