You stop searching through folders and asking a colleague who “had it somewhere.” You ask in plain language, and the answer comes with a reference to the document it came from.
Problem
In companies that work intensively with documents, time disappears in two places. On top of that comes chaos in mailboxes: documents arrive by email, some get stuck in private folders, some get lost in threads.
The answer exists, but in a contract from years ago, in a quality procedure, in meeting minutes, in an email nobody remembers anymore. Only nobody knows where. So the employee asks someone who “recalls something,” or digs through folders for half an hour.
The same data travels from document to spreadsheet, from spreadsheet to system, from system to email. With each retyping the risk of error grows, and with each missing document the case stalls, often without anyone knowing.
Anywhere there are already too many documents for everyone to know where everything is
Companies pass this point unnoticed: a year ago it was enough to ask one person, now nobody has the full picture, and answers have to be searched for in several places at once.
What the solution does
Search in documentation
One at a time or in whole batches.
No need to know the file name or the folder structure.
The specific document and the location the answer comes from.
It says so directly, instead of guessing.
PDF, Word (DOC, DOCX), Excel (XLS, XLSX), text files (TXT, MD). Multiple files at once.
Additionally, the knowledge source can include content from your website, WordPress, and entries added manually in the panel.
Rules for employee verification
You decide what goes into the knowledge base, and the assistant does not go beyond it. It’s worth understanding this difference before implementation.
Data security
Contracts, financial data, HR documentation. That’s why with this solution, security is the first consideration, not the last.
The assistant does not reach into the internet or other sources.
Each client's data is separated.
Document content does not go out to an external model provider.
Documents do not leave your network.
The local variant in practice
The most common concern with this solution is: “will our documents leave the premises?” We already have experience with projects where the AI model runs exclusively on the client’s local infrastructure, and the data does not leave the internal environment.
We built a media repository with automatic captions for a university. Lecture recordings get automatic captions in Polish, and the transcription model runs entirely on the university’s infrastructure. No material leaves its servers.
This implementation involves audio and video material, not text documents, but we cite it as evidence that we can run a model entirely within the client’s environment and process its materials there without sending anything outside. The same architecture underlies the local variant described above.
Dedicated implementation
Some companies need more than access to knowledge: they need the document to be recognized, checked for completeness, and passed on to the right person and system. This is a separate solution, designed for a specific process. Scope and pricing are determined after analysis.
The same rule applies at every stage: data extracted from a document is approved by an employee before it enters the system. The solution prepares the work; the decision and responsibility stay with the team.
We base this on integration projects delivered in ERP, CRM and document workflow systems.
We start with an audit of one process
We check what documents circulate, in what form, along what path, and where they get stuck. Based on this we propose the scope of the pilot. It’s usually one document type or one department, with success criteria set in advance.
The most common finding of the audit: some of the answers the team gives from memory do not exist anywhere in written form.
We will check where in your process the most time disappears.
