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You have thousands of documents and years of institutional memory. It's all scattered, and nobody can find it when they need it. When the person who knows takes leave, work stops.
Every company has the knowledge. Spec sheets in a folder, price history in a spreadsheet, the quality procedure on somebody's desktop, last year's contract on whoever's laptop. The new hire asks, the senior explains it one more time. When the person who knows takes leave, work stops. The problem isn't that the knowledge is missing. It's that it can't be found.
Gain: The archive becomes something the team uses every day.
with your own data · your data stays with you · a source on every answerA general AI has never seen your documents. And it won't say so: it produces something that looks plausible. In manufacturing, wrong technical data means a wrong quote, and a wrong quote costs money. The advisor we build doesn't speak from general knowledge. It speaks only from your verified documents.
PDF spec sheets, scanned contracts, spreadsheet price lists, email archives, the quality manual. You don't need to tidy them first. Each document is split into meaningful pieces, and each piece keeps a record of which section of which file it came from. Creating that order is the work itself, not a prerequisite for it.
Every answer states which document it rests on. You click, and you see that section as it is. It won't say anything it can't source. That isn't a presentation choice; it's a condition of how the system is built.
It doesn't produce an answer to a question your documents don't cover. That isn't a shortcoming; it's the most important thing about it. An advisor that invents an answer once is never trusted again, and the team quietly stops using it.
Access is decided together during setup. Sales sees the price list, not the HR files. Your documents stay on your own server and are never sent to train an outside model.
In the browser, on WhatsApp, or inside the software you already use. Wherever the team works. If it needs a separate place to log into, nobody logs in.
Folders, the shared drive, the email archive. Taken in whatever shape they're in.
Each document is split into pieces that carry meaning and stored with its source. Which sentence came from where stays on the record.
Keyword search and meaning search run at the same time and the results are merged. One person types "bolt length" and another says "screw size", and both land in the same place.
It doesn't go beyond the sections it found. The model doesn't write freely; it speaks from the document in hand.
A test set is built from real questions, and the right answers are written together with you. The advisor doesn't reach anyone until it passes. The set stays afterwards, too: it runs again every time the system changes.
Geolex works in real-estate law: 7,500+ legal records, 46 statutes, 172 court rulings, live. The copyright advisor brings Turkish copyright law, high-court rulings and EU directives into one place; it works across 2,600 articles and rulings, catches a fabricated case number, and has been used in a real case. SMAPATH guides SMA patients and their families through 4,800+ sources drawn from 85 institutions, live. We don't start from scratch for each new field.
Your documents stay on your own server and are never sent to train an outside model. We decide together, during setup, who gets access to what.
A conversation to understand where you are and decide the first step together. We'll talk as long as you need.
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