Credentials, customer names and identifiers do not leave your computer. The Schleuse detects them locally, replaces them with stand-ins that keep the meaning and translates the cloud AI’s answer back.
65 seconds · with sound · made-up example · The film is narrated in German · Portrait version for your phone: watch 9:16
Before a prompt leaves the house, the Schleuse reads the text with several detectors one after another. Everything runs on your own hardware; no cloud service is involved. The results are merged.
IBANs, email addresses, metering-point numbers, tax numbers and credentials follow fixed formats and are found reliably.
Open detection components (Presidio, GLiNER) find names in running text, in comments and in log lines.
A language model on your own hardware reads the text once more and catches what patterns and the name detector miss.
Instead of a bracket there is a general, related word: “Agricultural machinery business Alpha” instead of “Müller Landtechnik GmbH”. The meaning of the text stays readable, and the cloud model answers more usefully. Amounts, dates and quantities with units stay unchanged.
Made-up, simplified example. General terms reveal the type of the parties involved; with rare roles or sole traders this can be enough to identify someone. Then the coarser level is safer.
The key between original and stand-in word stays with you. The cloud AI’s answer is translated back locally. A round-trip test checks that out and back gives exactly the original. If a stage fails or a remainder is left in the text, nothing goes out when in doubt.
If the way back differs from the original, the request is stopped and named in the report.
If a hit from the key remains in the outgoing text, nothing goes to the cloud model.
The log records accesses and approvals, without contents, and is protected against later changes.