Image Recognition

We worked with a property services firm to build an image recognition pipeline that automatically assesses property conditions from photographs — replacing hours of manual review per property.

The challenge

Assessors were manually reviewing hundreds of property photos per day, classifying damage types, estimating severity, and writing condition reports. The process was slow, inconsistent across assessors, and created bottlenecks during peak seasons.

What we built

We trained a custom computer vision model on tens of thousands of labeled property images, capable of identifying structural issues, surface damage, and maintenance needs. The system generates condition scores and detailed findings that assessors can review and approve rather than create from scratch.

Results

• Assessment time reduced from 45 minutes to under 5 minutes per property
• Consistency across assessments improved by 60%
• Assessors handle 8x more properties during peak season