AI-Powered Floor Plan Analysis for Property Valuation

Property valuation models historically rely on gross external square footage and basic room counts. However, modern automated valuation models (AVMs) require granular spatial data: exact room geometry, window-to-wall ratios, ceiling heights, and layout efficiency metrics.

By applying specialized computer vision models directly to listing floor plans, AI can automatically segment room polygons, measure net usable floor area, classify space usage, and detect architectural features such as double-height ceilings or en-suite bathrooms.

The result is a structured spatial vector payload that feeds directly into commercial valuation algorithms, improving AVM precision by up to 14% over standard public tax records.