AI in manufacturing.

Evaluate inspection, maintenance, and planning agents against production records and quality exceptions.

Example workflow

Where agents work.

QC vision agent: Inspects parts on the line, flags defects, and routes rejects to a human reviewer through MES and SCADA.
Predictive maintenance: Reads sensor and downtime telemetry and schedules maintenance windows before a line fails.
Scheduling optimizer: Sequences orders by changeover cost, due date, and machine availability, subject to human confirmation.
Supply-chain triage: Reads PO and shipment exceptions and prioritizes supplier calls for planners.
OEE copilot: Identifies whether availability, performance, or quality is reducing OEE and locates the affected line.

Defect-detection accuracy: Catch rate on labeled rejects, relative to peers.
Downtime reduction: Unplanned downtime hours avoided through agent-triggered maintenance.
Throughput impact: Production-rate delta versus the human-only baseline.
Override rate: Frequency of inspector overrides of agent defect calls.
Policy-violation rate: Audit failures or out-of-spec passes, which cap tier.

Measurement depends on your source records and mapping. These are signals to evaluate, not automatically collected metrics.

Source coverage and outcome attribution depend on the records you provide.

We’ll review your source data and agree what to measure.