AI data market worth $24 billion faces a real problem: data is fragmented, costs too much, and moves way too slow. A fresh approach is reshaping this landscape—converting idle global bandwidth into a distributed data processing network. The model is straightforward: enable a massive community to collect and validate real-world datasets while keeping the infrastructure decentralized. This cuts through the current inefficiencies. Hundreds of thousands of contributors can participate directly, making data sourcing faster and more accessible. It's a direct challenge to how data collection and enrichment traditionally work in the AI space.