The Janitors Who Trained Their Own Replacements: How We Cut €890K in Cleaning Costs While Nobody Was Looking
A case study in autonomous facility operations and the labor apocalypse hiding in plain sight
The night shift supervisor at one of the largest Prague’s Office Houses didn’t notice when the cameras started watching back.
Week one: computer vision system learning cleaning patterns. Week four: scoring completion quality against ISO standards. Week seven: generating optimized routes that cut labor hours by 22%. Week twelve: the system knew which restrooms needed attention before the cleaning staff arrived.
By month six, the AI was better at managing cleaning operations than the humans who’d done it for fifteen years.
The cleaning crews were still employed.
They just weren’t deciding anything anymore.
The algorithms scheduled.
The robots cleaned.
The humans validated what machines had already verified.
This is ICOP.
The Intelligent Cleaning Operations Platform. Where €3.4 billion in annual facility cleaning costs met autonomous operations and one of those things stopped being necessary.
The €3.4 Billion Invisibility Problem
One of our customers, largest operators of office space in the world, spends €3.4 billion annually on cleaning across their global portfolio. Thirty percent of that is pure waste. Not from lazy workers or bad contractors. From structural inefficiency nobody wants to examine.
