The situation
A pool or heat network produces many readings. The council asks: Why are costs rising?
How it works
You paste an extract of the readings.
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
Explain these readings in plain words. What stands out?
Facility Familienbad Beispielburg, metering point DE0012345678901234567890123456789: Heat consumption July 18,400 kWh, previous year 14,200 kWh.
Facility Facility Alpha, metering point MeteringPoint_1: Heat consumption July 18,400 kWh, previous year 14,200 kWh.
This example is made up.
What you get
You get a plain explanation and ideas for what to check.
Good to know
The AI only sees the numbers you give it. You clarify the cause on site.
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
Explain a council proposal simply
The AI turns a long proposal into a text for everyone.
Read more →Municipalities and the public sectorAnswer a citizen's inquiry
The AI writes a draft reply.
Read more →Office and administrationHave an invoice checked
The AI reads the invoice and shows what stands out.
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/explain-facility-data.md