Context: Inspection pass rates are often read as proof of quality, but they reveal whether execution was controlled early enough, before inspection became the first point of intervention.

Challenges: Production keeps running to plan, quality inspects at scheduled points, and supervisors respond once defects are visible, so small deviations are tolerated until the cost is already embedded in time, material, and capacity.

Solution: The Quality Inspection Guidance Agent, an AI agent built using Microsoft Copilot Studio, monitors parameter drift and operator variability as they emerge and intervenes during the production run, flagging repeat minor deviations before first-pass yield is lost.

Impact: Construction teams adopting this approach see teams act when variation begins rather than when inspection rejects output, with results improving because execution gets earlier, not because inspection gets stricter.