Nothing on this page is real data. It is a working sketch of what the Coffee Knowledge Vault looks like once 5,000 people along the chain have contributed to it. No one has contributed yet — that is the phase we are in.
What method gets the score, at your altitude
Mean cup score by processing method across every lot in the vault. A farmer filters this to plots within 150 m of their own elevation before deciding what to try next season.
What buyers are searching for
Roasters query the vault by profile rather than by broker relationship. These are the searches that returned too few lots this month — each one is a market opening visible from the growing side.
How far back a bag can be walked
Every hop carries a date, a quantity and a source. Where a machine reading backs the claim, the lot is marked verified rather than stated.
| Lot | Origin | Process | Score | Flavour | Traceable | Buyer match |
|---|---|---|---|---|---|---|
| LOT-2026-0412 | Chiang Rai, Thailand | honey | 86.5 | longan · tamarind | 5 hops | Osaka · 2 roasters |
| LOT-2026-0388 | Huila, Colombia | washed | 85.9 | citrus · red fruit | 6 hops | Berlin · 4 roasters |
| LOT-2026-0361 | Yirgacheffe, Ethiopia | natural | 87.2 | jasmine · peach | 4 hops | Seoul · 3 roasters |
| LOT-2026-0344 | Nyeri, Kenya | washed | 86.8 | blackcurrant · tomato | 5 hops | Melbourne · 2 roasters |
| LOT-2026-0329 | Cerrado, Brazil | natural | 83.4 | nut · cocoa | 3 hops | moisture reading pending |
| LOT-2026-0317 | Aceh, Indonesia | wet-hulled | 84.1 | cedar · herbal | 4 hops | Taipei · 1 roaster |
Every figure on this page is simulated. The point is the shape of the answer, not the numbers: one structure, contributed to by everyone along the chain, that a farmer can query for what to do next season and a roaster can query for what to buy — and both get an answer that carries its own evidence.