VLM Facade Defect Detection

We built an AI system that turns raw building inspection photos into annotated defect reports, detecting 15 distinct pathologies (building cracks, sealant degradation, brick spalling, mortar erosion, steel corrosion, and so on) with accurate bounding boxes across facade inspections.

I’ll show the architecture of how we’ve setup the inspection image processing pipeline: the multi-pass detection architecture, the model training process, the defect annotation catalog, the eval harness we use to verify accuracy on new datasets & catch regressions. And why this was our selected way to set it up. I’ll walk through the examples of real reports going from photo dump to structured outputs (where the model gets it right and where it still needs a human check).