The AGIsGEM verification engine.
AGIsGEM combines real-world data ingestion, verification logic, and audit-friendly proof outputs so tokenization platforms, lenders, and marketplaces can make better decisions faster.
Data ingestion layer
AGIsGEM ingests structured signals from the systems already governing real-world assets — NLIS cattle records, sale yard data, weight & health histories, commodity reference rails, carbon registries, and counterparty disclosures. Sources are schema-normalised, timestamped, and stored alongside their provenance so every downstream score is traceable to its inputs.
Verification engine — the G.A.M.E. framework
Each contract or asset is processed through a three-layer model:
- Perception — extract and normalise the underlying records.
- Cognitive Auditor — apply rule-based and statistical checks: provenance integrity, weight & health consistency, sale cross-validation, counterparty risk flags.
- Action Layer — emit a Logic Score, risk flags, and a structured proof artefact.
Logic Score
The Logic Score is a 0–100 composite reflecting verification confidence across provenance, integrity, and risk dimensions. Each score is published with its rubric version, the data window it was computed against, and the specific flags driving its result. A score is not a recommendation — it is a transparent, reproducible signal.
Proof anchoring
Final reports are hashed and pinned to IPFS. The hash is referenced in an on-chain memo on Base so any counterparty can independently verify the report has not been altered since publication.
Outputs
- Logic Score PDF + machine-readable JSON
- IPFS hash and on-chain transaction reference
- API endpoints for lenders, insurers, and marketplaces
- Verification Log entry on agisgem.io/proof