One thing that caught my attention about @vangrid_io is that the real product may not be the video itself, but what can be built from it. Once a capture gets accepted, the buyer receives a textured 3D mesh in GLB format instead of the original footage. The raw video stays with the person who recorded it, while the reconstructed model becomes the actual deliverable. That changes how I look at the whole process. A video can show you what a place looks like from one perspective, but a 3D model can potentially become something machines use to understand and interact with that environment. The interesting part is the balance between detail and usability. Reconstructing a scene is one thing; preserving the small objects, surface textures, edges, and spatial accuracy that robots or AI systems may depend on is another. To me, this is where the real value of spatial data will be decided. Not simply by how realistic a model looks on screen, but by how useful and reliable it becomes when put to work in the real world. If @vangrid_io can turn everyday phone captures into dependable, reusable 3D assets while keeping original footage private, it could help make real-world data far more practical for robotics and AI. The camera captures the world. The model is what helps machines make sense of it.