22 years building operator adoption systems across 12 countries. Founded AVPMi. Deployed in airports, hotels, hospitals. Sold 2016. Now AI is hitting the exact same wall — extraordinary technology that operators can't use. I built the bridge once. I'm building it again.
I'm looking for one AI company willing to solve the operator adoption problem properly.
Every AI company fights over the same 5% — technical users who understand prompts, APIs, databases. The other 95% are warehouse managers, hotel operators, hospital staff, parking operators. They know their operations better than any AI model. But there's a translation gap nobody is building.
I built AVPMi to solve one problem: parking and valet operators couldn't adopt the software being sold to them. Not because they were resistant — because nobody was building it for them.
By 2016 AVPMi was deployed across 12 countries. Airports, hotels, hospitals, parking operators on three continents. I sold the company. Sailed for seven years. Watched the AI revolution arrive — and watched it walk straight into the same wall.
After the AVPMi exit I sailed for seven years. Read everything I could on machine learning. Watched extraordinary models ship — and watched operator adoption stall at 5%, just like it did in 2003.
The technology had changed. The wall hadn't. So I came back. Same playbook, new tools. Four showcases in six months. Zero lines of code written by me.
The 200th feature meets the first edge case meets the third pivot. That's where most builds collapse — not from bad code, but from the operator never having been in the room. 72Knots is the methodology that keeps the tower standing — 22 years of operator instinct telling the AI what to build, what to throw away, and what NOT to do. Four showcases, three live and one built in public, prove the method works. Same playbook, different verticals.
One valet family: ValetParking.ai on-premise, Cloud Valet AI hosted, and Ticketless.
What it proves:A full enterprise valet system, rebuilt by an operator with AI, holds up in live operations.
Hotel & casino operations: every guest request routed to the right department, with Sophie answering guests.
What it proves:The same playbook works in a different department of the same hotel.
Check-in and claim for anything a guest hands you and expects back.
What it proves:One idea, the phone number as the claim ticket, covers cars, coats, bags, skis and repairs.
The first open-source, enterprise-level parking system ever built.
What it proves:The method scales to a fully integrated self-parking system.
The proof isn't a pitch deck. It's episodes of building real enterprise systems with AI, in public, without a developer.
Parking and hospitality are the showcase verticals — proof the method works under operational pressure. The same playbook scales across manufacturing, logistics, healthcare, retail, and every other industry where the 95% problem exists. What I can't do alone is run it everywhere. That takes resources, domain experts, and time. I have 2–3 years to embed this inside the right company.
If you're working on AI adoption with business operators, or you're an operator who wants to understand what AI can actually do for your operation — reach out.
Fort Lauderdale, FL USA
Direct: 📧 Show email | (954) 612-5464
