Introduction
Marco Belloni found the old reservation book in a moving box, sticky at the edges from kitchen air. On some evenings the restaurant had been understaffed; on others he had bought too much. The book did not accuse him. It simply kept the pattern.
Marco lives in Lugano and advises small restaurants on automation and planning. He does so as someone whose own restaurant closed after rising costs and a badly timed expansion.
Story of the Path into AI
After bankruptcy, Marco analysed old orders, duty rosters and reviews. He saw connections he had missed while trying to keep the place alive. Weather, local events, reservation habits, staff exhaustion: none of these alone explained the failure, but together they mattered.
He learned no-code tools, demand forecasts and the limits of automated review analysis. Many people thought he was the wrong person to advise restaurants because he had failed. Marco decided the failure was precisely why he had to be honest. His first project combined weather, bookings and local events for staff planning. It broke down when a private celebration nearby changed foot traffic. He added a manual note field after that.
Current Work
Today Marco works with small restaurants that cannot afford expensive systems. For a pizzeria he built a cautious delivery-time forecast. When uncertainty is high, customers receive a longer time window rather than a false promise.
One business reduced food waste and overtime without cutting service staff. Marco avoids selling this as magic. AI can help sort signals, but it cannot write an honest calculation, negotiate rent or heal a chaotic menu. Planning still belongs to the people who carry the risk.
Personal Advice
“AI can organize numbers, but it will not do honest costing for you,” Marco says. His advice is to start where money actually leaks: waste, waiting time, overstaffing, understaffing, promises the kitchen cannot keep.
Key Facts
Age and place: 45, Lugano.
Background: bankruptcy, family business, restart with debt experience.
Entry into AI: analysis linking weather, reservations and local events to staffing.
Focus today: gastronomy and planning.
Typical tools: no-code AI, demand forecasts, review analysis.
Werkstattnotiz
Marco keeps the page from a night the forecast would have missed entirely. A local club won a match, and the restaurant filled after closing should have begun. He now asks every client what the model cannot know about the neighbourhood. The answer often matters more than the software.