TotalPave

NCTech offers a service that collects high-resolution 360° street-level imagery and LiDAR data to document infrastructure assets in the field. It uses geospatial capture techniques to map the exact location, orientation, and status of items like signs, poles, utility boxes, sidewalks and more. The data collection process replaces many site visits by enabling desktop review of assets, and feeds into updating inventories and condition assessments with minimal manual input. The captured imagery and 3D data can be regularly refreshed so agencies can monitor change over time and integrate the outputs into GIS or asset-management systems.

Viso Suite is a computer vision platform that enables automated pothole detection using video feeds or images from cameras mounted on vehicles or infrastructure. The platform allows users to build and deploy detection models that identify and locate potholes in real time, measuring their position and dimensions. It supports integration with mapping and workflow systems so maintenance teams can visualize detections, generate alerts, and plan repairs directly from the captured data.

RoadAI uses a smartphone to survey road networks, capturing video while driving and applying computer vision to automatically identify surface distresses such as alligator cracks, potholes, settlement, and edge deterioration. It also detects roadside assets including traffic signs, line markings, guard rails, street lights, manholes, and drains. The system provides interactive maps and exportable data formats such as Excel, CSV, GeoJSON, and Shapefile for integration with asset management workflows.