Module
Violation processing
The stage where an event becomes evidence. AI narrows the queue; a person decides. Every decision, including every rejection, is recorded with its reason.
Two levelsReviewer and supervisor quality control, on a sampled or full basis according to the program.
Reasoned rejectionEvery discard carries a coded reason, and the reasons are reportable.
Feedback loopHuman corrections return to model training.
The queue
Volume is managed by removing the obvious, not by rushing the rest
Classification separates clear non-events from what needs judgment. The reviewer's time goes to the cases that actually require a person, which is what keeps quality up as a program scales.
Pre-filtering
Low-confidence reads, occlusions and duplicates are separated before review.
Evidence package
Images, metadata, calibration record and signage state, assembled by the system for the reviewer.
Disposition
Approve, reject or escalate, each with its coded reason.
Trained reviewersTraining requirements documented per program, as several state statutes require.
Named accountabilityEvery decision is attached to a person and a timestamp.
Reportable qualityApproval rates, rejection reasons and review times, per site and per reviewer.
See a review queue in operation
We will show you the workflow with anonymized sample data.