Recall Affected Population Classification

Recall Affected Population Classification uses AI to identify and classify which product units, serial number ranges, and customer accounts are within the scope of a product recall, enabling faster and more complete recall notifications, by matching recall scope criteria against production, sales, and registration records, across recall management and regulatory reporting workflows.

Recall management teams manually cross-reference production batch records, customer registration data, and sales channel records to define the affected population for each recall action. The process is slow, requires significant manual data reconciliation, and risks excluding affected units or including unaffected units, both of which have regulatory and reputational consequences.

The AI ingests the recall scope definition (affected batch ranges, production periods, component suppliers) and classifies each unit in the product and customer database as within scope or out of scope, producing a validated affected-population list with the evidence trail for regulatory submission.

Time to produce a validated affected-population list decreases; recall scope classification error rate decreases.

• •Product serial number and batch records are linked to customer registration or sales records at unit level.
• •Recall scope definition templates are standardised across recall triggers (component, date range, plant).
• •Regulatory submission format requirements are codified for each relevant market.