The situation
You need a query for a report. The example contains table and customer names that should not leave the house.
How it works
You describe the tables and the question.
The Schleuse replaces secrets
Names, addresses, identifiers and credentials are replaced with stand-in words. This happens on your side, not in the cloud. Amounts and dates stay as they are.
The AI answers, the Schleuse translates back
The answer contains the stand-in words. On your side they turn back into the real names.
Example
Write an SQL query: revenue per customer in 2026, sorted in descending order.
Table kunden_mueller_landtechnik with columns kunde_name, revenue, year. Wanted: revenue per customer in 2026.
Table Table_A with columns Column_A, revenue, year. Wanted: revenue per customer in 2026.
This example is made up.
What you get
You get a query and an explanation.
Good to know
Try the query on a test database first. Never run unchecked queries on real data.
Zone of this use case: Yellow
Only through the Schleuse. And only to targets you have approved.
Status of the Schleuse
Version 0.1 Alpha. So far tested only with made-up examples. Not reviewed by third parties. No legal advice.
Related use cases
Analyse an error log
The AI finds the cause. Passwords and customer names stay secret.
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The AI looks for errors and insecure settings.
Read more →Software development and ITHave code explained and reviewed
The AI explains code or suggests improvements.
Read more →Would you like to try this?
We are looking for pilot partners. We test the Schleuse with made-up or cleared examples first. Only then does real text go through.
This page is also available as Markdown for AI reading systems. /en/use-cases/get-help-with-sql.md