This startup offers an AI-powered drone platform that automates structural inspections by capturing 3D models and analyzing imagery to identify critical damage. Their solution eliminates the need for manual inspections, providing a safer, faster, and more cost-effective way to assess infrastructure integrity.
Funding
Funding not disclosed
Founders
Product
Problem
Traditional structural inspections of critical infrastructure rely on manual methods such as rope access or scaffolding, which are slow, expensive, and expose workers to hazardous conditions. These methods also produce subjective and inconsistent results, hindering effective maintenance and risk management.
Solution
Prenav offers an automated drone-based inspection platform that leverages deep learning and 3D modeling to digitize and analyze critical infrastructure. The platform enables users to fly off-the-shelf drones to capture thousands of high-resolution images, which are then processed into a 3D digital twin of the asset. Proprietary deep learning algorithms automatically scan the digital twin for defects such as cracks, corrosion, and missing components, delivering objective, repeatable insights and tracking changes over time. An enterprise-class web interface allows users to visualize the 3D point cloud, share measurements, and generate reports, facilitating data-driven decision-making and proactive maintenance.
Target Audience
The primary target audience includes infrastructure owners, engineering firms, and inspection service providers responsible for maintaining bridges, dams, cell towers, and other critical assets.
Features
- Automated drone flight planning and data capture using commercially available drones
- High-resolution 3D reconstruction (point cloud) of structures from drone imagery
- Defect detection and classification using a flexible deep learning pipeline
- Sub-millimeter resolution for identifying even the smallest surface anomalies
- Enterprise-class visualization tools for browsing and inspecting digital twins
- Web-based interface for sharing 3D models, measurements, and reports
- Synthetic imagery generation for augmenting deep learning training datasets