The problem: AI is amnesiac by nature
One of the major limitations of Artificial Intelligences (LLMs) is that their knowledge stops dead on the day they finish being trained. If a model was finalised last summer, it will know nothing at all about the burning news of spring 2026. Worse still: it has absolutely no way of knowing about the confidential sales file you created yesterday on your protected network.
For a long time, when an AI did not know the answer to a question that was too recent or too private, the logical continuation of its mathematics dictated that it invent a plausible answer rather than stay silent. This is what data scientists call a "hallucination".
The solution: RAG (Retrieval-Augmented Generation)
To solve this problem at scale in the enterprise, engineers have industrialised a formidable technique: RAG. Concretely, it is like giving your AI its own private internal search engine, which it will use before it is allowed to answer you out loud.
In French, it translates as Génération Augmentée par la Recherche. The intelligence of the base model is "augmented" by forcing it to "go and fetch" tangible information beforehand. The AI no longer speaks off the top of its head, it works with its books open!
How does it work? The library analogy
Let us imagine you ask your enterprise agent: "How much did the supplier Alpha cost me last month?". Here is what happens under the bonnet in a few milliseconds:
- The Library (Vector indexing): Beforehand, the system has hoovered up all your private archives (invoices, emails, PDF reports), chopped them up and filed them in immense virtual drawers called vectors.
- The Librarian (Retrieval): When you ask the question, the system does not make the AI think straight away. A swift search algorithm (the librarian) dashes to the shelves and instantly pins down the drawers talking about "supplier Alpha" and "recent expenses".
- The Expert Reader (Generation): The librarian takes out the right documents found (which serve as legal evidence) and hands them to the large artificial intelligence model.
- The Unfalsifiable Answer: The large AI model reads the documents just placed under its nose, and intelligently writes back: "According to invoice no. 402 (here is the link to verify it), the supplier cost 15,000€".
The end of data leaks onto the internet
Thanks to RAG, the business world has crossed a threshold. Today, it is no longer necessary to send all your secret files to the giant brains of OpenAI or Google to teach them your trade (which posed serious problems of industrial espionage). The AI's "brain" remains generic and empty, and it is your internally secured library that feeds it in real time, just so that it can answer the question of the moment.