Drawings, site safety and programme risk.
AI for Construction & Engineering
Construction data is visual and contractual. The wins are in reading drawings and specifications quickly, and in seeing site risk sooner.
What makes this sector different
Specifications are long and inconsistent
A tender pack runs to thousands of pages across formats.
Site conditions change daily
Safety and progress data is captured on phones, not systems.
Margin is decided at tender
Missed requirements at bid time become losses at delivery.
Where it pays back
Tender and specification review
Retrieval-augmented generationSurface obligations, exclusions and risk clauses across a full tender pack.
Site safety monitoring
Computer visionDetect PPE compliance and hazard conditions from site camera and phone imagery.
Progress verification from photos
Computer visionCompare site imagery against programme to flag slippage.
RFI and submittal assistant
Retrieval-augmented generationAnswer queries from the contract documents with the clause referenced.
How the Construction & Engineering assessment differs
Construction assessments weigh document volume against how much of the useful data is images captured in the field.
Data sources we expect
Questions this template pushes on
- How much of your source material is drawings or scans?
- Is site imagery captured consistently enough to model against?
- Where does a missed requirement cost you most — tender or delivery?
These are suggestions surfaced alongside the questions — never pre-filled answers. The assessment still asks you everything, because a score built on assumptions you never confirmed is not a score you could act on.
Scope an AI project for construction & engineering
The Construction & Engineering template sharpens the questions. Ten minutes gets you a feasibility score, an architecture and a costed plan.