The biggest challenge for physical AI is diverse data collection. Spatial Web is a pipeline for photorealistic, physically accurate environments — captured from real, lived-in homes and delivered for model training.
Train in a reliable digital copy of real space — layouts, clutter, and lighting as they actually occur — and minimize hours in the physical environment.
Photoreal environments for large-scale video data collection, with camera intrinsics simulated to match your capture rig.
Measured geometry and real floor plans: the loop closures, occlusions, and awkward layouts synthetic scenes don't produce.
Listing-derived labels and verified market records as supervision — ground truth without an annotation pass. The layer no scene library has.
Statuses are literal. What's marked operating can be demoed on a call.