Mastero.AI replaces slow, inconsistent manual visual inspection with an AI confidence-routing engine — auto-approving high-confidence results and routing only ambiguous cases to your QA team.
Mid-market manufacturers lose 30–90 seconds per part to manual visual QA — and still miss defects. Annotation errors compound into training data debt. Most teams have no path to AI without massive investment.
Manual inspection averages 30–90 seconds per part. A single shift produces thousands of inspection decisions — all prone to fatigue and inconsistency.
Human annotators disagree on borderline defects. Those disagreements propagate into training data, degrading any downstream AI model quality over time.
Manual QA leaves no traceable record. Warranty disputes, recall investigations, and compliance audits require data your current process can't produce.
Every image runs through AI inference. The confidence score determines the routing decision — automatically, in seconds, with a full audit trail.
Image submitted → AI inference → Confidence score → Routing decision
Thresholds are configurable per deployment — no code changes required.
No promises without proof. Every milestone is measured against a hard target before the next phase begins.