AI that knows your documents
Companies want AI, then hit two problems: a standard chatbot does not know your internal documents, and you must not upload sensitive data into it. This page explains how that is solved - without technical jargon.
What the problem is
Ask a standard AI chatbot about your internal policy and one of two things happens: it says it does not know, or it invents an answer. It cannot do otherwise - it has never seen your documents.
Nor can you simply upload them. Contracts, payroll, project documentation - none of that belongs on someone else's server, whether you look at it through GDPR or common sense.
And yet this is exactly what would help companies most. Not AI that writes poems, but AI that knows what you know - and answers in three seconds instead of half an hour of searching a shared drive.
How it is solved, in plain language
The approach is called RAG and the principle is simpler than the acronym suggests. Think of it as an assistant with an open library:
Your documents are organised
Contracts, policies, manuals, minutes - split into smaller passages and stored so they can be searched by meaning rather than by exact wording.
You ask a normal question
"What is the notice period in the contract with supplier X?" No keywords, no forms. Just a question.
The system finds the relevant passages
It retrieves the sections that relate to your question - even if they do not contain the exact words you used.
The AI answers and shows its source
It composes the answer from those retrieved passages, not from memory. And it links to the document it drew on, so you can verify it.
This is the essential difference: the AI is not asked to recall, but to read this and answer. That is why it does not invent, and why you can check the answer against the source.
Where your data stays
The most common question, and entirely legitimate. I design the solution so that your documents stay in your environment - typically in your own cloud account, in an EU region.
- Documents are not used to train any public model.
- Access rights can be enforced - payroll material is visible only to those entitled to see it.
- It is possible to trace who asked what.
What companies actually use it for
- Internal knowledge base. A new joiner asks instead of going round their colleagues.
- Contracts and documentation. "Where did we agree the response time?" instead of searching five versions of a PDF.
- Customer support. Faster answers, because the agent is backed by the documentation.
- Regulations and standards. An answer with a reference to the specific provision.
Openly: when it does not make sense
I will not sell you AI at any price. It does not make sense when:
- Your documents are not digital, or they are out of date. Over outdated documents, AI only provides a faster route to the wrong answer.
- You are doing it for prestige rather than to solve a problem. Start with what slows us down, not with we want AI.
- Proper search or a tidy-up of the shared drive would solve it. Cheaper and more reliable.
This is not theory. I built such a system myself, end to end - from document processing to production deployment. I know where the pitfalls are, because I ran into them.
Frequently asked questions
Can our documents leak?
Not with a proper design. Data stays in your environment, is not used for training, and access is governed by permissions like any other system.
How do we know the AI is not making things up?
Every answer includes a link to the source document. If the source does not match, you see it immediately. That is the main reason it is built this way.
What does it cost?
It depends on data volume and the number of users. Running a smaller solution is typically in the low thousands of CZK per month; the larger part of the cost is the one-off deployment.
How long does it take?
A pilot over a selected set of documents can be built in weeks. I recommend starting small and expanding once you see it works.
Will it replace our people?
No. It saves them searching. A person still has to decide and verify - which is why the link to the source matters so much.
Considering AI and unsure where to start?
I will tell you plainly whether it makes sense in your situation and what it would involve. No enthusiastic promises.
Book a free consultation →