Entero Therapeutics’ Grid AI enter LOI with AI data-center customer

Entero Therapeutics (ENTO)’ Grid AI has executed a Letter of Intent with a stealth-mode hyperscaler artificial intelligence data-center developer to deploy Grid AI’s advanced power-cluster optimization and orchestration platform at the customer’s first large-scale AI campus. The campus-expected to be among the more sophisticated AI-ready digital-infrastructure sites in development-will be located in the ERCOT market in Texas. The definitive commercial contract is expected to be executed in early 1Q26. The stealth mode customer’s initial Texas campus is scheduled to begin generating revenue for Grid AI in 3Q26 with approximately $8M in annual revenue in 2027, scaling to over $50M in 2029, with multiple additional campuses already in the customer’s development pipeline. The LOI outlines a multi-phase strategic partnership to develop a best-in-class orchestration platform that unifies power-cluster design, coordinated dispatch, commercial optimization, and data analytics. The platform’s architecture reflects key elements described in the LOI between the stealth mode customer and GridAI, including: An initial deployment site in Texas, used to validate and scale up a world-class optimization engine designed specifically for large-scale digital-infrastructure assets. Development of a scalable, high-performance infrastructure model integrating behind-the-meter generation, storage, and flexible load management to deliver cost-efficient, resilient, and grid-supportive power solutions. A unified technoeconomic simulation model to quantify $/MWh, reliability, and PUE impacts across various asset configurations and commercial structures. A next-generation dispatch-control and commercial-optimization engine capable of co-optimizing grid imports, battery assets, and gas-generation blocks, while coordinating financial and physical hedge positions. A secure, cloud-based data-capture and reporting platform providing continuous operational visibility and market transparency for data-center operators.