Datavault AI 与 Triton Geothermal 签署价值数百万美元的代币化服务协议，开辟可观的收入机会

Core Insights - Datavault AI Inc. has established a leading position in the valuation, digitization, and monetization of real-world assets (RWA) through a tokenization service agreement with Triton Geothermal LLC, a geothermal energy company based in Houston, Texas [1][2] - The agreement allows Datavault AI to earn up to $8 million in tokenization fees, corresponding to an expected total face value of approximately $125 million in digital token issuance, along with a 5% share of all transaction fees from the digital tokens post-issuance [1][2] Group 1: Agreement Details - The digital token issuance aims to fund the development of Triton's geothermal energy production assets, which are located in a verified geothermal reservoir [2] - Triton has completed a market assessment to determine the economic viability of the resource, providing a basis for the underlying assets of the tokens [2] - Datavault AI will serve as the exclusive technology provider for the tokenization of Triton's current and future renewable geothermal energy portfolio [3] Group 2: Strategic Implications - The partnership is expected to enhance the transparency, compliance, and operational control of tokenized renewable energy assets [3] - Datavault AI anticipates that similar tokenization agreements will increasingly contribute to its revenue structure as institutional participation and regulatory clarity in the digital asset space grow [3] - The integration of structured digital assets with renewable energy development plans is seen as a viable approach to accelerate energy production in the U.S. [3] Group 3: Company Overview - Datavault AI leads the development of AI-driven data experiences, asset valuation, and monetization in the Web 3.0 environment [4] - The company's cloud platform integrates acoustic science and data science, offering comprehensive solutions across various industries, including energy [4][5] - Datavault AI's technology suite supports customized functionalities, including AI and machine learning automation, third-party integration, and data analytics [5]