Methodology
Tiny Fish is one of Switzerland's most thoughtful sushi brands — 14 stores, growing 4–5 per year, fed by a central kitchen in Altstetten that reaches Geneva by 11:30. The next decade hinges on choosing the right next sixteen stores well.
Tinystores is a multi-criteria decision model. It evaluates any Swiss commercial-lease offering against the principles that actually drive Tiny Fish unit economics: how many pedestrians walk past, who they are, what they can spend, how easy the location is to reach by public transit, how much office activity sustains weekday lunch, what competition already exists, how visible the shopfront is, and how flexibly the lease is structured. Hard filters reject anything outside the 3-hour kitchen radius or too close to an existing store.
Competition is modeled in two directions, not one. Direct competitor proximity (other sushi or Asian-cuisine operators within 200 m and 500 m) is a penalty — head-to-head splits demand. But a moderate cluster of any nearby restaurants and cafés is a positive signal: it proves the location is a validated lunch zone, not an isolated bet. Tiny Fish wants to be the best fresh option inside a proven corridor, not alone in an empty one.
The signal layer is built on a foundation of public Swiss federal data, free OpenStreetMap geographies, and a small number of paid APIs already in operation — running at a marginal cost in the low double-digit Swiss francs per month. No broker fees. No expensive third-party panels. The current run uses live OpenStreetMap amenity density, real drive-time routing from Altstetten, and direct competitor classification. Federal demographics, SBB station volumes, and live commercial-lease listings will be wired in over the next two phases.
Demo: 20 Swiss candidate locations, scored
Twenty plausible Swiss commercial locations evaluated by the model. Bottom 10 are openly shown — proof the model rejects what it should. Middle 7 are openly shown — the gradient of what's interesting but not best. The top 3 are currently under internal audit — they'll be revealed (gated) once validated against Tiny Fish's operational filters.
Top 3 — under audit
The top 3 are being manually validated
The model has converged on three specific Swiss addresses as top candidates. Before publishing them, we're hand-auditing each against Tiny Fish's operational filters and confirming the underlying signals. They'll be revealed (gated, by request) once validated.
Notify me when ready →Middle 7 — solid candidates, score 66-84
The gradient — interesting locations the model rates above the line, just not the very top.
Bottom 10 — why these score poorly
Locations the model rejects. The labels show why — that's how the model validates itself from below.
For context: the 15 existing TF stores
Where Tiny Fish is today — the reference set the model is calibrated against.
Are you interested to learn more?
The white paper is a 1,000-word read on the model's philosophy, data approach, validation strategy, and the 2040 vision behind it. The top 3 candidate locations are a conversation.
Yes, let's talk →