AI Progress Monitoring
AI systems that compare as-built site conditions captured by drones, cameras, and 360-degree scans against the BIM model and construction schedule to automatically measure percent complete and identify deviations.
Definition
AI progress monitoring transforms site documentation from a labor-intensive manual process into a continuous, data-driven operational system. These platforms combine photogrammetry, computer vision, and AI analysis to process imagery from multiple capture sources and automatically compare what's built to what was planned. DroneDeploy's Progress AI uses VLMs to track 80+ trade types and delivers reports within 2 hours of imagery upload, without requiring BIM models or schedules. Buildots processes site walks from helmet cameras to generate per-location trade completion percentages, predictive delay forecasts, and root cause analysis. For owners and lenders, AI progress monitoring enables automated payment application verification—replacing monthly site walk-throughs with continuous percentage-complete data. For contractors, early warning is most valuable: identifying that a subcontractor's productivity rate implies a 3-week delay 6 weeks before the scheduled milestone, when corrective action is still affordable. Buildots reports 50% reduction in project delays across deployments.
Examples
AI progress report showing structural concrete is 94% complete on floors 1-8 with predicted floor 9 completion 4 days ahead
Buildots detecting MEP rough-in on floors 3-5 is running 11 days behind schedule based on camera walk data
Owner's lender requiring AI-verified progress reports instead of manual pay applications, reducing disbursement cycle from 3 weeks to 4 days
Nomic Use Cases
See how Nomic applies this in production AEC workflows:
Frequently Asked Questions
AI progress monitoring transforms site documentation from a labor-intensive manual process into a continuous, data-driven operational system. These platforms combine photogrammetry, computer vision, and AI analysis to process imagery from multiple capture sources and automatically compare what's built to what was planned. DroneDeploy's Progress AI uses VLMs to track 80+ trade types and delivers reports within 2 hours of imagery upload, without requiring BIM models or schedules. Buildots processes site walks from helmet cameras to generate per-location trade completion percentages, predictive delay forecasts, and root cause analysis. For owners and lenders, AI progress monitoring enables automated payment application verification—replacing monthly site walk-throughs with continuous percentage-complete data. For contractors, early warning is most valuable: identifying that a subcontractor's productivity rate implies a 3-week delay 6 weeks before the scheduled milestone, when corrective action is still affordable. Buildots reports 50% reduction in project delays across deployments.
AI progress report showing structural concrete is 94% complete on floors 1-8 with predicted floor 9 completion 4 days ahead. Buildots detecting MEP rough-in on floors 3-5 is running 11 days behind schedule based on camera walk data. Owner's lender requiring AI-verified progress reports instead of manual pay applications, reducing disbursement cycle from 3 weeks to 4 days.
Project Research: Instantly access all project-critical information from a single search interface. Automated Drawing Review: Automatically review drawings against building codes, internal standards, and client requirements.