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Cloud & Data · Construction & real estate

AI-Powered Construction Progress Monitoring

Drone imagery and computer vision that compare actual site progress against the plan, catch delays before they get expensive, and give owners, contractors, and investors one reliable view of every active project.

Drone aerial view of a commercial construction site with AI zone-by-zone progress overlays
Weekly
AI-analyzed drone flights replacing ad hoc site visits
Portfolio-wide
single dashboard across every active site
Days, not weeks
from raw imagery to an executive-ready report
Field superintendent reviewing AI-generated site progress on a tablet at the construction site
The challenge

What the client was facing

A construction company managing several large commercial developments needed a reliable, weekly view of what was actually happening on site. Progress updates were pieced together from manual walkthroughs, subcontractor photos in chat groups, and spreadsheets — subjective, inconsistent, and always a few days out of date.

By the time a real delay surfaced in a status meeting, it had often already cost money. Leadership needed a way to compare built reality against the plan objectively, flag risk early, and give clients and investors evidence-based reporting instead of a verbal summary.

What we built

The solution

  • Drone imagery ingestion pipeline turning weekly flights into a consistent visual record of each site
  • Computer vision models that detect structural elements and measure completed work by zone, floor, and work package
  • Planned-vs-actual comparison against schedules and milestone data, with automatic delay and deviation flagging
  • Progress dashboards with map and zone overlays for project managers, executives, and clients
  • Automated report generation for stakeholder updates — no more manually assembled slide decks
  • Portfolio view for centralized oversight across every active site, with role-based access for owners, contractors, and consultants
In production

What it looks like

Illustrative screens — actual client dashboards, branding, and site data are anonymized for confidentiality.

Executive progress-monitoring dashboard shown on a boardroom screen, with zone-by-zone completion, AI insights, and risk predictions

Executive dashboard — planned vs actual progress, AI-detected issues, and productivity analytics in one view

Field superintendent reviewing site progress, milestones, and AI insights on a tablet at the job site

Field view — the same planned-vs-actual data, simplified for a tablet on site

AI-first delivery angle

Why AI-first mattered here

The hard part isn't showing a pretty dashboard — it's turning noisy aerial imagery into measurements people can trust. Senior engineers owned the computer vision pipeline, model evaluation, and the data contracts linking imagery to schedules and BIM/CAD references, while the AI does the repetitive measuring and comparison work.

Every flagged delay or deviation is traceable to a specific flight, zone, and model version, so project managers can verify a finding before they act on it — the platform surfaces risk, humans keep the final call.

Technologies

Stack

Python OpenCV PyTorch Photogrammetry / Orthomosaic PostGIS FastAPI React AWS

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