How InferTrust™ creates verifiable records for AI-assisted supply chain quality decisions including incoming inspection, supplier quality, and lot disposition.
Manufacturing supply chains increasingly use AI for incoming material inspection, supplier quality scoring, lot acceptance decisions, and traceability. When these AI systems make quality decisions that determine whether materials enter production, the consequences of an incorrect decision can propagate through the entire manufacturing process.
InferTrust™ (Patent Pending) Industrial captures the decision event when an AI system evaluates incoming materials: the inspection model used, the quality criteria applied, the measurements or visual inspection results, and the disposition decision (APPROVE_RELEASE, HOLD_FOR_INSPECTION, or REJECT). This creates a verifiable record that links each lot of incoming material to the specific AI evaluation it received.
Over time, InferTrust™ decision records build a comprehensive quality intelligence database for each supplier. Organizations can analyze AI quality decisions by supplier, material type, time period, and production line to identify trends, support supplier negotiations, and make data-driven sourcing decisions backed by verifiable evidence.
When a quality issue requires a recall or containment action, InferTrust™ records enable precise identification of which lots were evaluated by which model version under which quality criteria. This precision can significantly reduce the scope of recalls by providing verifiable evidence that certain lots were properly inspected and met quality standards.