StruxAI's computer vision platform detects cracks, corrosion, and spalling — then automatically links every finding to your SNBI element inventory and generates fully NBI-compliant reports. The only platform that does this.
StruxAI didn't build incremental improvements to the status quo. We rebuilt inspection infrastructure from first principles.
Every defect StruxAI detects is automatically mapped to its SNBI element — deck, superstructure, substructure, or culvert component — with correct element numbers, condition states, and quantities pre-populated. No manual element mapping. No post-processing. No other platform does this.
Upload your bridge's Revit model directly into StruxAI. Inspection photos are automatically geolocated and attached to their corresponding BIM element — creating a living digital twin of your asset. Navigate the 3D model and see every defect in context, tied to the exact structural member it was found on.
No other inspection platform forecasts what comes next. StruxAI's predictive engine analyzes inspection history, traffic loading data, environmental exposure, and material age to model deterioration curves and predict maintenance needs years in advance.
From raw field images to SNBI-linked reports, predictive forecasts, and portfolio dashboards — explore the platform below.

Over 620,000 bridges. Most inspected by hand, documented on paper, with condition ratings that vary by inspector, not by bridge.
A standard bridge inspection — field work, documentation, and NBI report — takes 3–7 days plus weeks of report writing. Undetected defects propagate.
The same bridge evaluated by two qualified inspectors produces different SNBI element condition ratings over 30% of the time. Subjectivity is a systemic problem.
FHWA spends $5.2B+ annually on bridge inspection. A significant portion goes toward manual documentation that doesn't improve maintenance outcomes.
Drag-and-drop photos from inspection cameras or smartphones. Or upload your bridge's Revit model. StruxAI accepts JPEG, TIFF, RAW, IFC, RVT, and NWD. Batch processing up to 10,000 images.
StruxVision™ — trained on 2.4M+ FHWA-annotated images — detects cracks at 0.1mm resolution, corrosion, spalling, and joint failure. Every finding is automatically linked to its SNBI element with correct condition states. 340ms inference.
A complete SNBI/NBI-compliant report is generated: element inventory, condition ratings with quantities, GPS-mapped findings, risk score, maintenance recommendations, and predictive deterioration forecast. Push to AASHTOWare.
StruxVision™ detects and geo-locates every defect, maps it to its SNBI element, assigns condition states, and outputs it directly into your NBI inspection report.
Automate your biennial SNBI inspection cycle without expanding headcount. SNBI-linked reports, prioritized maintenance queues, and predictive capital forecasts from one platform.
Learn how →Transform field photos into SNBI-compliant, element-linked deliverables in minutes — letting your licensed engineers focus on engineering judgment, not documentation.
Learn how →Pre-construction condition surveys protect you from change-order disputes. StruxAI creates a timestamped, SNBI-documented record of every existing defect before construction starts.
Learn how →Municipalities managing aging infrastructure use StruxAI to build complete condition histories, forecast capital needs, and prioritize maintenance based on SNBI-linked AI analysis.
Learn how →See SNBI element auto-linking, BIM integration, predictive maintenance forecasts, and full report generation — live, with your own images if you'd like.
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