Vertical AI · Construction & Engineering
BIM & Clash Detection from Construction PDFs — Without the BIM Project
Coordination and clash detection traditionally require full BIM models, specialist modelers, and weeks of setup — so on most mid-market projects, they simply don’t happen, and the clashes are found in the field instead. We’ve built AI that works from the drawings you already have: structured PDF sets in, a navigable 3D systems view and coordination flags out.
The problem: coordination is priced out of most projects
BIM is expensive to get into
Full clash workflows assume a Revit/Navisworks pipeline: modeled architecture, structure, and MEP. That means specialist modelers, weeks of lead time, and a budget line most mid-market jobs never had.
Most projects live in 2D PDFs
The drawings exist — dense, structured, information-rich PDF sets. But everything a coordinator needs is locked in linework and schedules that only an experienced human eye could read. Until now.
Clashes get found in the field
A duct main meeting a beam, a cable tray fighting a sprinkler run — discovered during installation, each one triggers RFIs, rework, and schedule slip. Field-found clashes are the most expensive kind.
Rework eats the margin
Industry studies consistently put rework at several percent of total construction cost — much of it traceable to coordination issues that were visible in the drawings all along.
What AI changes: the drawings become the model
Our extraction stack — built and battle-tested inside Aginera, our construction takeoff platform — reads structured PDF drawing sets the way an estimator and a coordinator would: sheet by sheet, discipline by discipline, symbol, route, and schedule together.
Structured extraction from the PDF set
Devices, equipment, and the routing that connects them — recovered per discipline with real drawing coordinates, powered by the same patent-pending drawing-intelligence work behind RouteNet.
A systems-level 3D view — no modelers involved
Extracted systems are lifted into a navigable BIM-style 3D representation of the floor: what runs where, which systems share the same corridor and ceiling space, all derived from the 2D set you already have.
AI-assisted coordination checks
Cross-discipline interference and congestion candidates are flagged automatically — duct vs. structure, tray vs. piping, stacked services in tight zones — and presented with drawing evidence for a human coordinator to review and disposition.
Takeoff and coordination from one extraction
The same structured extraction that powers the clash view also produces quantities and bills of materials — one pass over the drawings, two deliverables that used to be separate projects.
Who this is for
MEP & specialty contractors
Catch the conflicts that would hit your crews before you price and sequence the work — using the bid set, not a model you’ll never be given.
General contractors & developers
Get a coordination signal on projects that would never justify a full BIM execution plan — and push sharper questions back to the design team before ground breaks.
Owners & PE-backed operators
Portfolio construction and fit-out programs get a repeatable, low-cost review layer across every project — instead of coordination quality depending on which GC you drew.
Built in production, not in a lab
This capability runs inside Aginera, where our extraction pipeline processes real commercial drawing sets daily — and it’s the same vertical AI discipline we describe in the RouteNet story: purpose-built models where generic AI fails, precision-first engineering, and humans kept firmly in the loop. If you’re a PE firm or operator wondering what this pattern looks like in your own industry, start with our vertical AI for private equity page.
Frequently asked questions
Does this replace Navisworks or a BIM coordination process?
No — and it isn’t trying to. Where a full, contract-mandated BIM execution plan exists, use it. This is for the far larger set of projects that will never get one: it produces a systems-level 3D view and reviewable coordination flags from 2D PDFs, so human judgment is applied where it matters instead of nowhere at all.
What do you need from us to start?
Just the PDF drawing set — the same structured sheets you’d bid from. No models, no CAD exports required (though native DWG/DXF files improve fidelity when you have them).
How accurate is it?
Extraction quality is measured continuously against real project benchmarks in Aginera, and every coordination flag carries its drawing evidence so a reviewer can confirm or dismiss it in seconds. It’s engineered as a review-assist: high-value flags with receipts, not unreviewable claims.
Can this be adapted to our company’s workflow?
Yes — that’s Kamna’s core business. We deploy Aginera directly, and we build custom vertical AI on the same foundations for contractors, engineering firms, and PE-backed construction businesses with their own document types and rules.
Bring us one drawing set
Send a representative project PDF set and we’ll show you what the extraction, the 3D systems view, and the coordination flags look like on your own drawings.