The economics of high-fidelity, ground-level spatial data have always been unfavorable. Dedicated mapping fleets are expensive to operate and slow to scale into every neighborhood or industrial site. Satellite imagery is relatively cheap but cannot see under trees, into building entrances, or around temporary obstacles. The outcome is that large portions of the physical world remain poorly observed for the purposes of Physical AI. @vangrid_io bounty system creates an on-demand market. Organizations specify exactly what they need, including location, type of capture, and deadline, and fund the request in USDC. Contributors compete to fulfill it. Payment is released only after the requester accepts a submission. Because the work is performed by people who are already present with phones they already own, the marginal cost of obtaining a new, targeted observation falls dramatically compared with dispatching a specialized vehicle. Public figures from the network show more than 1.25 million captures, hundreds of thousands of users, thousands of attestations, and over $600,000 in USDC already settled through the system. The network is no longer a concept. It is a functioning market for verified spatial ground truth. That market structure is what allows continuous coverage to emerge without the capital intensity of traditional mapping.