SiteScan provides an AI‑driven platform that automates infrastructure inspections by processing images and sensor data with computer‑vision and machine‑learning models to identify cracks, corrosion, deformation, and compliance gaps. The system generates annotated, actionable reports and integrates with asset‑management tools, helping contractors, facility managers, and owners reduce labor costs, speed up inspection cycles, and improve safety and regulatory compliance.
Funding
Funding not disclosed
Founders
Product
Problem
Manual site inspections require extensive labor, are prone to human error, and often result in delayed identification of structural issues, compliance violations, and maintenance needs, leading to increased safety risks and higher operational costs.
Solution
SiteScan offers an AI-powered platform that automates the capture and analysis of infrastructure data using computer vision and machine learning. The system processes images and sensor inputs to detect structural defects, compliance gaps, and maintenance requirements without the need for manual measurement. Detected issues are compiled into detailed, actionable reports that highlight risk areas and recommended remediation steps. By streamlining inspection workflows, SiteScan reduces labor expenses, shortens inspection cycles, and improves overall site safety and regulatory adherence.
Target Audience
Primary customers are construction contractors, facility managers, and infrastructure owners who need efficient, reliable inspections of buildings, bridges, and other critical assets.
Features
- Automated image capture and processing using computer-vision algorithms to map site conditions
- Machine-learning models trained to identify cracks, corrosion, deformation, and other structural anomalies
- Real-time compliance checking against industry standards and building codes
- Generation of customizable inspection reports with visual annotations and prioritized action items
- Integration APIs for exporting data to existing asset‑management and maintenance systems