Funding
Funding not disclosed
Founders
Product
Problem
Manual inspection of rooftops for damage, material composition, and potential issues is time-consuming and requires on-site presence. This process limits efficiency for professionals needing to assess multiple properties for maintenance, insurance claims, or solar installation planning.
Solution
BIRDIA provides an AI-powered platform that analyzes high-definition aerial imagery to automate rooftop assessments. The system processes images with up to 5cm resolution, identifying structural damage, material anomalies, and other relevant features without requiring physical site visits. This enables rapid, data-driven decision-making for roofing contractors, insurance adjusters, and urban planning departments. By leveraging advanced image recognition and machine learning, BIRDIA delivers detailed diagnostics and actionable insights directly to users.
Target Audience
The primary target audience includes roofing contractors, insurance companies, and municipal or public sector entities involved in urban planning and infrastructure management.
Features
- AI-driven analysis of high-definition aerial imagery for rooftop condition assessment.
- Automated detection of damage, material degradation, and anomalies with 5cm resolution accuracy.
- Capability to analyze public aerial imagery (PCRS) and LiDAR data for urban planning applications.
- Identification of objects of interest such as public roof conditions, at-risk vegetation, and degraded road surfaces.
- Generation of real-time, actionable reports for maintenance prioritization and risk assessment.
- Integration with existing aerial data sources for streamlined workflow.
- Machine learning models trained on industry-specific expertise for precise diagnostics.