Datavault AI Inc. (NASDAQ: DVLT) announced that it has executed a binding term sheet with Scilex Holding Company (NASDAQ: SCLX) for a $120 million cash contribution and revenue participation agreement. The funding is expected to support the deployment of Datavault AI's quantum-ready, zero trust edge network across an estimated 100 U.S. cities, enabling advanced AI, high-performance computing, and secure data processing capabilities.
Under the agreement, Scilex will receive a tiered share of network revenues up to defined caps. The partnership aims to accelerate the build-out of critical infrastructure for AI and data-intensive applications, addressing growing demand for secure and high-speed computing at the edge.
Datavault AI specializes in AI experience, valuation, and monetization of assets in the Web 3.0 environment. Its cloud-based platform provides solutions through its Acoustic Science and Data Science Divisions. The Acoustic Science Division features patented technologies including WiSA, ADIO, and Sumerian, focusing on spatial and multichannel wireless HD sound transmission. The Data Science Division leverages Web 3.0 and high-performance computing for experiential data perception, valuation, and secure monetization.
The company's Information Data Exchange (IDE) enables Digital Twins and licensing of name, image, and likeness (NIL) by securely attaching physical real-world objects to immutable metadata objects. Datavault AI's technology suite offers AI and ML automation, third-party integration, analytics, and marketing automation.
The $120 million term sheet represents a significant investment in edge computing infrastructure, which is crucial for real-time data processing and AI applications. The deployment across 100 U.S. cities could have wide-ranging implications for industries such as healthcare, fintech, energy, and entertainment, which rely on low-latency and secure data handling.
For more details, the full press release is available at https://ibn.fm/LOPm4. Latest news and updates on Datavault AI can be accessed at https://ibn.fm/DVLT.
