Inspection quality review has always been one of the more difficult management responsibilities in CEI work. Project managers are responsible for reviewing inspection submissions before approving them for the pay request, checking that quantities are reasonable, narratives are sufficient, required forms are complete, photos are present, and nothing has been omitted that could create a problem downstream. On an active project with daily inspections from multiple crews across multiple locations, this review burden is substantial, and the reality is that things get missed. Not because PMs are not diligent, but because the volume of material makes comprehensive review difficult at the pace that field work generates it.
Oversite's AI inspection review agent addresses this by providing an automated first pass on every inspection that enters the review queue. When an inspection is submitted for approval, the agent runs automatically, analyzing the record for quality issues, narrative gaps, quantity anomalies, missing certifications, and potential discrepancies against adjacent inspection records or established project norms. The findings are surfaced to the PM before they ever open the inspection, prioritizing what actually needs attention rather than requiring the PM to read every record from scratch.
The agent is also conversational. PMs can ask it to explain a specific finding, probe why it flagged a particular item, or discuss the implications of a discrepancy before deciding how to handle it. This means the review process becomes a guided dialogue rather than an independent assessment from scratch, and PMs can direct their judgment to the issues the agent has identified rather than re-examining records that are already clean.
The downstream effect on pay request quality is meaningful. Inspections that reach the pay request stage have already passed through three layers of review: the inspector who documented the work, the AI agent that analyzed it for quality and consistency, and the PM who makes the final approval decision. Documentation gaps are identified and corrected before they become audit findings. Quantity anomalies are flagged before they create billing disputes. The standard of documentation that goes out the door is higher, consistently, not just when there is time to review carefully.