Fraud & Anomaly Detection for Healthcare & Hospitals

Every flagged decision needs an explanation an investigator can act on. 'The model said so' fails in a case file and fails harder in a regulatory review.

In healthcare & hospitals, clinical safety and patient privacy mean nothing ships without human oversight and a complete audit trail. 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 discharge summary drafting, usually integrated against EMR and EHR. We start from the constraint, not the capability, what the system must never do, who signs off, and what happens when it is wrong.

Deployed across regulated and unregulated sectors, with audit trails where the regulator expects them. You own the code, the models where they are open-weight, and the documentation to run it without us.