Food Data Flow
What data moves through a bottle's life, and where does each reading earn its keep?
Data Footprint
| Layer | Current State | DePIN State | Gap |
|---|---|---|---|
| Schema | Producer ERP, retailer POS | Shared SPL NFT + custody event schema | No cross-industry schema |
| Data | Batch averages, paper BOL | Per-unit sensor logs, on-chain custody | Siloed in spirits/wine |
| API | EDI, proprietary B2B | Public blockchain reads | No open food API standard |
| UI | Retailer dashboards | Scan-to-verify consumer apps | Few consumer-grade tools |
| Feedback | Insurance claims, lawsuits | Real-time market signals, AI anomaly | Producers outside the loop |
Decisions the Data Drives
| Data | Decision | Action |
|---|---|---|
| Custody chain complete | Premium price confirmed | Unlock secondary trade |
| Temperature excursion | Quality risk | Insurance payout, batch flagged |
| Molecular mismatch | Counterfeit | Seize, delist, alert network |
| Price history + anomaly | Fair value calculation | AI pricing engine, collector buys |
| Sensor offline streak | Storage trust degraded | Vault penalty, node slashing |
Context
- Food Principles — Nomenclature and data model
- Data Footprint Commissioning — Maturity instrument
- DeVin Labs Sensor Layer — RedBite RFID reference
Questions
Which decision in the supply chain is most blocked by missing data today?
- If sensor data is free, does insurance pricing still make sense?
- What is the first food category where the feedback loop closes without a retailer in the middle?