RAG: why your AI needs to know your company
“An AI that only knows the web — what use is that for my business?”
The observation
An AI model on its own only knows what it learned during training: the web, books, articles. Your customer history, your rates, your internal procedures, your contracts — it doesn't know them. Asked about your company, it will answer confidently… by making things up. That's exactly the problem RAG solves.
How we handle this topic
What RAG is, concretely
RAG stands for "retrieval-augmented generation". Before answering, the agent goes to find the information in YOUR documents and YOUR data, then formulates its answer from what it found. It doesn't draw on its memories: it reads your sources.
What it changes, in practice
The agent can cite your rates, your lead times, your real terms. And when the information isn't in your sources, it says so instead of making it up. That's the difference between a general-purpose assistant and an agent that knows your business.
We add rules, not just technology
RAG isn't enough on its own. We add business rules: who has the right to see what, which questions are out of scope, when a human must validate. These rules are what make the agent reliable over time.
Your data stays with you
RAG runs on your infrastructure or on France hosting. Only the question asked leaves — never your documents. That's what makes it usable on sensitive data.
Memory updates with your changes
When you change a rate or add a document, the agent takes it into account at the next synchronization. No need to retrain a model: that's the advantage of the retrieval approach.
What it changes for you
- The agent answers from your real documents, not from assumptions
- It can say "I don't know" when the information isn't in your sources
- Your data isn't used to train a third-party model
- Content updates without retraining
The limit, stated plainly: Answer quality depends entirely on source quality. An outdated document, an unreadable PDF, a poorly maintained database will produce disappointing answers — RAG doesn't fix the data upstream. That's why the assessment often starts with the state of your documents.
Is your situation specific?
This topic is handled case by case. The assessment frames it around your numbers, not in the abstract.