Automated construction progress tracking

The problem

Large builds are too detailed for a handful of managers to track accurately; progress reporting is subjective, disputes over what’s “done” are common, and delays cascade expensively. McKinsey estimates on-site mismanagement costs the industry ~$1.6 trillion a year.

The AI approach

Site managers wear a 360° helmet-mounted camera during normal walks; computer vision matches the footage to the BIM model and schedule across 80+ construction stages, automatically measuring percent-complete, flagging deviations, and forecasting delay risk by trade and location.

Evidence it works

Buildots reports reductions in project delays of up to ~50% (2–3 months on average projects); Intel reports avoiding ~4 weeks of delay per fab; an NCC project saw task completion rise sharply and reporting time fall ~70%; Sir Robert McAlpine deployed it across 260,000+ m² for tracking, billing and QA.

What “good” looks like

An objective, time-stamped source of truth for status; earlier delay warnings; less time on manual reporting; fewer disputes with subcontractors.

Feasibility & cost shape

Enterprise pricing per project (camera hardware + subscription); best value on mid-to-large commercial, residential, infrastructure and data-centre builds.