Guillermo Vidal
Guillermo Vidal

I ran the kitchen. Now I build the software it runs on.

Kitchen operations, data, and the software in between. Menu data rebuilt for a group across five cities, where 15% of the menu had no cost and 23% of recipes could not compute one. A kitchen system I built and ran through a live production shift. Currently ETH Zurich CAS in AI and software development.

EU work rights via dual citizenship. Zurich, on site or hybrid. I'm also open to relocating. ES / EN / PT, German in progress.

Selected work

Restaurant National — the kitchen itself

At Restaurant National I built the pre-order sandwich shop: a site that only sold pickups the kitchen could fulfil. I also ran the kitchen it served, holding food cost at 34%; that ground-level view is what I build from.

Most food sites sell a menu. This one only accepted orders the kitchen could actually prep and hand over in 15-minute slots.

I built the pre-order sandwich shop for Restaurant National in Wattwil: three sandwiches, drinks, consecutive 15-minute lunch slots on Thursday and Friday between 10am and 2pm, pay, collect. No delivery. The kitchen only saw paid orders, grouped by slot, and the amounts to prepare at component level.

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The constraint was the product. Ten sandwiches per 15-minute slot. Daily SKU caps (chicken 50, pork 30, veggie 30). Same-day cutoff at 10.30am Switzerland. The site checked those limits in the interface, again on the API, and reserved them atomically so two guests could not take the last Fried Chicken. After 10.30am, same-day ordering disappeared.

The kitchen side was the other half: a slot-grouped order view, short spoken IDs, confirmation mail that does not double-send if the payment webhook retries, and a payment flag that could run disabled, demo, or live so we could rehearse without charging guests.

Recorded before a polish pass; the order-viewer rows are dummy data. The shop ran live for two months, until the restaurant was sold.

KOS — kitchen operating system

One truth for the whole menu: ingredients, recipes and costs connected, trusted everywhere. I built KOS full-stack and ran it through a real production shift.

The real production run: bones to demi-glace.

Status: a working prototype and portfolio piece, not a product.

Menu-data engagement — multi-country restaurant group

The group could not cost a large part of its own menu, so margin reporting rested on estimates. My engagement: connect recipes, costs and sales into one dataset it can rely on.

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