Core Problem & Solution - AI model commoditization and decreasing compute costs highlight data as the primary bottleneck [1] - The company addresses the data bottleneck by coordinating data collection, labeling, and curation using crypto incentives [4] - Crypto and blockchain technology facilitate the placement of data and IP on an immutable ledger, enabling tracking, attribution, and licensing via smart contracts [7] Competitive Advantage & Market Opportunity - Meta Scale AI's partial acquisition created a vacuum in the AI data space, presenting an opportunity for competitors [6] - The company's decentralized approach allows collaboration with any IP, offering flexibility [15] - The company has already secured contracts, indicating market demand [13] Data Acquisition & Application - The company uses crypto incentives to coordinate data collection on a global scale, compensating contributors with stablecoins or other crypto tokens [6] - The collected data, including egocentric video footage from diverse settings, is crucial for training AI models, such as humanoid robots [9] - Contributors set licensing usage terms on the blockchain, ensuring IP safety [12] Business Model & Demand - The company acts as an agent to secure contracts, connecting data providers with AI model developers [13] - Many organizations are willing to work with the company, some dropping contracts from Scale AI [14][15]