Fraud & Anomaly Detection for Logistics & Supply Chain

Rules encode known fraud patterns precisely; models catch the novel ones. Every system worth running uses both, and we are explicit about which is doing what.

In logistics & supply chain, your data depends on partners whose systems you do not control. That single fact reshapes how fraud & anomaly detection has to be built here, the guardrails, the approval points and the evidence trail are design inputs rather than things bolted on before go-live.

The workload we are most often asked to take on first is exception and delay handling, usually integrated against WMS. We start from the constraint, not the capability, what the system must never do, who signs off, and what happens when it is wrong.

Multi-model by default, so a provider outage is a routing decision rather than an incident. We hand over with runbooks, tests and a team that knows how it works, not a dependency.