Measurable selectivity
Track what was selected, why it was selected and what the control produced.
Selectivity and targeting for AI-enabled customs risk management.
MAATAI Sentinel helps customs teams move from static selectivity to measurable targeting: scores, signals, explanations, overrides, feedback and continuous learning.
The declaration queue, risk score, explanatory signals and operational recommendation are brought together in a view designed for selectivity and targeting. Officers can see why a case has surfaced before they act.
The purpose of Sentinel is not to multiply controls, but to improve the quality and justification of targeting decisions.
Track what was selected, why it was selected and what the control produced.
Give agents and supervisors readable reasons for a score or alert.
Record data versions, scores, rules, overrides and control outcomes.
Use feedback to update risk patterns and targeting rules.
Risk management becomes stronger when product intelligence and case reconstruction are connected to the same decision chain.
Analyze product descriptions, documents and HS suggestions.
Rebuild the timeline and evidence trail of complex cases.
Keep targeting rules and AI outputs explainable and auditable.
A pilot can focus on one office, one flow, one product family or one risk scenario.