Solution
Catch problems before a recall catches you
Darwin doesn't just capture and trace, it analyzes your data in real time to detect anomalies, predict risks and answer complex compliance questions. AI that explains every alert by citing the applicable regulation.
Two pillars
AI applied to regulated compliance
More than dashboards: actionable intelligence
Traceability generates a lot of data. The value is in having someone, or something, review that data 24/7 and warn you before an auditor flags a problem or a retailer rejects a shipment.
Anomaly detection · In production
Deterministic rules engine that evaluates each Critical Tracking Event the moment it is captured. Spots ghost lots, cold-chain breaks, shrinkage, route deviations and expired certifications, with an actionable explanation.
Agentic compliance · Q3 2026
Agent that answers questions like "Does LOT-8901 qualify to export to the US?" crossing on-chain data + current regulation + risk analysis. Coming Q3 2026: request early access.
Pillar 1, Anomaly detection · In production
5 active categories, 11+ on Q3 2026 roadmap
Every alert comes with the exact reason, the regulation section referenced and the suggested action, so your team knows what to do without reading code.
Data integrity
Missing KDEs, duplicate lots, TLCs with inconsistent format between actors. Caught before they reach the audit.
Temporal
Violated sequences (Harvest > Pack), on-chain backdating, temporal gaps with no events, impossible transits by distance/speed.
Chain of custody
Ghost lots (receiving without shipping), custody gaps, unauthorized actors for that event type. The costliest failures to catch manually.
Quantity / mass balance
Excessive shrinkage between shipment and receiving, inflated yield on transformations, unit-of-measure mismatch. Early signals of fraud or error.
IoT / environmental
Cold-chain breaks, GPS route deviations, temperature out of range for commodity. Detected in real time from integrated IoT sensors.
Actionable explanation
Every alert arrives with severity (CRITICAL/HIGH/MEDIUM/LOW), FSMA 204 section referenced, lot history and a suggested action. Endpoint /explain available for per-alert deep-dive.
Pillar 2, Agentic compliance · Coming Q3 2026
Ask in natural language, get a compliance report
From junior to senior analyst, in seconds
Your team doesn't need to memorize 400 pages of regulation or navigate 10 systems, they ask the agent and get the answer with the trace of how it was obtained. Early-access tenants get priority on setup plus custom prompts per industry.
Request early accessNatural-language query
E.g.: "Does this organic spinach lot meet the requirements to export to the US?", the agent routes the query across multiple data sources.
Automatic multi-source crosscheck
The agent queries on-chain data (chain of custody, lab results, actors), current regulation (FSMA 204, EUDR, private certifications) and risk modules (anomalies + rules).
Structured compliance report
Output with status (COMPLIANT / NON_COMPLIANT / REQUIRES_REVIEW), gap analysis (what's missing), risk scoring, regulation citations and concrete recommended actions.
Pipeline
How it works end-to-end
1. Event ingestion
CTEs captured by Captia and anchored by Tracium enter the pipeline, with temporal, geographic and relational enrichment.
2. Deterministic detection
Deterministic rules engine (5 active categories, 11+ on Q3 2026 roadmap) runs on each Critical Tracking Event. Semantic detection with embeddings arrives in Pillar 2 Q3 2026.
3. Combined score
If rules + semantic both flag → high severity. If only one flags, it stays on watch. Filters to minimize false positives.
4. Actionable explanation
Every alert arrives with severity, regulation section referenced and lot history, all computed deterministically. Endpoint /explain available for LLM + RAG deep-dive (citing regulatory text + actor profile). Full agent is Pillar 2 (Q3 2026).
5. Alerts and feedback
Notification by severity (Slack/email/webhook). Operator marks false_positive → feeds the model back. Confirmed anomalies enrich future context.
Have questions?
Find answers to all frequently asked questions about Darwin, grouped by topic.
View FAQLet AI watch over your chain
24/7, never tired, with an explanation for every alert. Let's talk about deploying it on top of your current data.