A branch of a 27 billion dollar enterprise was running its field operations on paper and Excel. We replaced all of it with one AI agent — and recovered over 100,000 euros a year.
Egasca is part of the Citizen Group. Yes — the watch company. Citizen has a market cap of 27 billion dollars. Egasca is the arm that builds industrial manufacturing machines across Europe.
Publicly traded company. Heavy industry. Real operations. They build and sell large, expensive equipment that factories depend on every day. Once a machine is sold, Egasca is responsible for keeping it running — repairs when something breaks, scheduled maintenance every few months, replacement parts. The full lifecycle.
When a customer's machine breaks down, Egasca sends a technician. On top of that, every machine needs regular maintenance — inspections every few months or years depending on the model. With thousands of machines in their portfolio, that's a constant stream of jobs.
To manage it all, they had an ERP. On paper, that should have been enough. In reality the system was clunky, slow, and the team avoided it. So tickets, materials used, hours worked, travel distances — all of it got documented in Excel spreadsheets, on paper, or not at all.
When you're tracking thousands of machines across paper and spreadsheets, things get lost. Customers get missed. Follow-ups don't happen. A technician drives out, replaces a part, and nobody logs which part or how long it took.
The challenge wasn't just building software. It was building an AI agent smart enough to run their operations without anyone babysitting it.
We audited the business, understood every decision a human was making in the process — and taught an AI agent to make those decisions instead.
All the manual tracking, the chasing, the errors from human data entry — gone. The 100,000 euros they were losing per year — recovered. And they did it without adding a single new software license to their stack.
We've shipped agentic AI products since early 2025. If the standard tools don't solve it, we go deeper.