'Can we have our own ChatGPT, but one that knows our products, prices and procedures?' — this is probably the most common question we've heard from clients over the past year. The answer is yes — and the technology behind it is called RAG (Retrieval-Augmented Generation).

The problem with general AI models

ChatGPT and its peers are incredibly capable, but they know nothing about your business: what your contract terms are, which product is compatible with which, what the complaint procedure is. And public versions raise the question of where the data your employees type into them actually goes.

How does RAG work?

RAG connects the language model to your knowledge base. When an employee or customer asks a question, the system first finds the relevant documents — contracts, manuals, product specifications — and feeds exactly those to the model. The result: answers grounded in your information, with sources cited, instead of hallucinations.

What does the business gain?

• Internal assistant: new employees find answers in seconds instead of asking colleagues — onboarding shortens dramatically.
• Customer support: the bot answers based on your documentation with accuracy general models cannot reach.
• Contracts and documents: 'Which clients have a discount clause above 10%?' — an answer in seconds, not an afternoon in folders.
• Security: the data stays with you — the system can run entirely on your own infrastructure.

Our approach

We build corporate assistants in stages: we start with one clear domain (for example product documentation), measure answer accuracy, then expand the scope. We integrate the assistant where your people already work — in the CRM, on the website, in Teams or Slack.

Your data is an asset that has so far been locked away in folders and systems. An AI assistant is the key that unlocks it — for every employee, at any time.