The situation
You have a list of customers and sales. You want to know: Who buys a lot? Where are sales falling?
How it works
You paste an extract from the table.
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
Which customers bring in the most revenue? What stands out in the numbers?
Meier, Jonas · Musterweg 12, 99999 Beispielstadt · Sales 2025: 4,200 EUR · Sales 2026: 3,100 EUR
Customer_1 · Address_1 · Sales 2025: 4,200 EUR · Sales 2026: 3,100 EUR
This example is made up.
What you get
You get hints about trends. The numbers stay unchanged.
Good to know
Tables are processed cell by cell. Test with a small extract first.
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.
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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/analyze-a-customer-list.md