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Architecture and construction

Train clash, hazard and defect detection models

Architecture firms, construction-tech companies and equipment makers: train on drawings, BIM models, site cameras and scans.

A synthetic drone orthophoto of a building site with a translucent BIM wireframe overlay and a Mon to Sun scrubber. One red marker: Clash, duct × beam, Level 3, grid C-4. Side card: Progress against model 62% (planned 68%); Flights this week 7; Open issues 1 clash, 2 hazards.

What it's worth

Cut the cost of rework and site injuries

Construction-tech companies sell contractors the savings from flagging clashes and site hazards.
of project cost goes to rework on average, within a 2–20% range
About 5%
saved on a USD 1 billion build when rework falls from 5% to 4%
USD 10 million
estimated cost of one fatal work injury, across all US industries
USD 1.54 million

Sources: Construction Industry Institute, via Curtin University review; National Safety Council Injury Facts, 2024 estimate; the second figure is arithmetic on the first.

Use cases

Design, site and machine models

  • Design checking

    Raw data
    Drawings, BIM models, specs
    Rare cases to find
    Clashes between disciplines, code breaches
    Adapt per
    Building code, client standard
    Release test
    Issues found against a checked set
  • Site safety

    Raw data
    Site and crane cameras
    Rare cases to find
    People in swing radius, no harness at height
    Adapt per
    Site, phase
    Release test
    Missed hazards on replayed footage
  • Progress tracking

    Raw data
    Drone flights, 360° walkthroughs, laser scans
    Rare cases to find
    Out-of-sequence work, deviations from BIM model
    Adapt per
    Project, building type
    Release test
    Progress against surveyed quantities
  • Quality inspection

    Raw data
    Photos and scans of concrete, steel and welds
    Rare cases to find
    Cracks, exposed rebar, bad welds
    Adapt per
    Material, contractor
    Release test
    Missed defects on an inspector-checked set
  • Machinery

    Raw data
    Machine cameras, lidar, telemetry
    Rare cases to find
    People in blind spots, unstable ground
    Adapt per
    Machine type, site
    Release test
    Collisions in simulation

How it works

Drawings and site footage in. Tested releases out.

Melt dataPrepare the data · 01–03

  1. 01Ingest

    Load drawings, BIM models, site cameras, drone flights and laser scans; drop corrupt files, catalogue by project, phase and date, and anonymise faces and plates.

  2. 02Mine

    Find clashes, near-misses, unsafe acts and defects in drawings and weeks of site footage, and drop near-identical files.

  3. 03Label

    Auto-label clashes, people, machines, protective gear and defects with large labelling models that run inside the platform; your engineers correct a sample.

Forge intelligenceTrain and test the model · 04–06

  1. 04Train

    Retrain your shared base model on the full, versioned dataset when data from a new site lands; every release traces to its exact data.

  2. 05Adapt

    Fine-tune the base model for each building code, site, phase and machine fleet, and tune it again as the project changes week by week.

  3. 06Validate

    Optimise each release candidate for site cameras and drones, then replay past clashes, incidents and inspector-checked defects against the last release.

Drawing to site

One BIM model for design and site

Design checks read the BIM model; progress and safety models compare drone flights and site cameras against it.

One copy of project data (drawings, BIM models, drone flights, site footage) feeds two lanes that point at one shared BIM model. Design lane: a drawing sheet with one clash circled, then the BIM model with the clash highlighted, tagged design-check v13. Site lane: a site-camera frame with a person boxed, no harness at height, then the BIM model with progress filled, tagged site-base v13, with three adapted children: Tower phase, Fit-out phase, Crane cameras.

Quality

Regressions stop at the gate

Every release candidate runs the last release's test sets; a drop beyond your margin blocks it until you sign off.

Your team sets the metric and margin for each test set, such as missed clashes, missed hazards, false alarms per hour and missed defects, each with its 95% confidence interval.

Architecture and construction

release v13 → release candidate v14 · lower is better

  • Missed clashes, checked design set

    Cases
    420 issues
    Last release
    18
    Release candidate
    14
    Margin
    +2
    Result
    Pass
  • Missed hazards, replayed footage

    Cases
    300 clips
    Last release
    9
    Release candidate
    14
    Margin
    +2
    Result
    Fail +5
  • False alarms per hour

    Cases
    50 h
    Last release
    0.6
    Release candidate
    0.4
    Margin
    +0.2
    Result
    Pass
  • Missed defects, inspector-checked set

    Cases
    900 photos
    Last release
    27
    Release candidate
    22
    Margin
    +3
    Result
    Pass

Release candidate blocked: 1 test set beyond its margin

Interface preview · sample data

Your data

Your project data and weights stay yours

Ownership
Your data, labels and trained weights stay yours. Bytemelt has no access to them: your contract says so, and the platform is built so only accounts your team controls can open them.
Anonymisation
Your team anonymises faces and plates at ingest with the platform's tools, using rules you set, or before the files leave your own systems.
Location
Your data is stored and processed only at the partner data centre your contract names, in the Middle East and outside the EU. The contract names the site and country before any data moves, and data leaves the site only when your team moves it. Personal data from the EU moves only under transfer safeguards such as Standard Contractual Clauses, and we give your data-protection officer the site details a transfer impact assessment needs.
How Bytemelt handles your data

Questions design and construction teams ask

All questions about Bytemelt
We're a contractor. Is Bytemelt for us?

If you want models of your own, trained on your site data, yes: the platform labels, trains and tests them automatically, with compute power included. Bytemelt sells the platform, not model training to order.

Do design checks and site models share data?

Yes. Both train on one copy of your project data: drawings, BIM models, drone flights and site footage.

Size compute for your project data

In one hour, the founder maps your drawings, site footage and models to the six stages and sizes the compute.

contact@bytemelt.ai