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NORCE Research: building location-aware AI for local food systems
Together with NORCE we proved that a location-based AI model can suggest practical, season-aware menus matched to local producer supply, a milestone toward unlocking local sourcing.
By Day of Week research team
Why location-aware menus matter
Chefs and hospitality teams want menus that sing with season, place and story. Yet many menu decisions still rely on spreadsheets and guesswork. In our proof-of-concept with NORCE we asked: can AI propose menus that are actually buildable using the local produce available, in season, and matched to guest tastes?
What we built and tested
We developed a prototype service that ingests producer metadata, kitchen constraints and guest preference signals to generate realistic, actionable menu proposals. The service creates a short supply chain — a call-off forecast pushed into the operational layer — so the kitchen’s proposed menu implies demand downstream to hubs and producers.
Outcomes
The pilot delivered practical proposals that chefs accepted with minimal edits, concrete data specs for producers and restaurants, and a feasibility blueprint for scaling to production services.
About this article
NORCE & Day of Week research collaboration, Agder
“We proved that location-aware menu recommendations aren’t science fiction — they’re practical and immediately useful to chefs.”
Øystein Løken — Founder & CSO