Auddia Inc. (NASDAQ: AUUD) announced today that its subsidiary LT350 has signed a non-binding Letter of Intent (LOI) with a NYSE-listed medical real estate investment trust (REIT) to host the first pilot installation of its solar-integrated AI micro-datacenter canopy. The pilot is expected to take place at a hospital property in the Dallas Fort Worth metropolitan statistical area. The medical REIT owns and manages approximately 200 medical facilities across the United States, including hospitals, ambulatory surgery centers, and medical office buildings.
The LOI outlines plans to deploy LT350's patented parking-lot-based AI micro-datacenter canopy, which integrates modular GPU, memory, and battery storage cartridges into the ceiling of a solar canopy. This design allows high-performance AI compute to be deployed above existing parking lots without absorbing parking spaces or requiring new land acquisition. According to the company, the pilot will focus on validating LT350's ability to support HIPAA-aligned inference workloads, reduce grid impact through solar generation and battery buffering, and preserve all parking functionality.
Jeff Thramann, M.D., CEO of Auddia and founder of LT350, said, "Healthcare is one of the most latency sensitive and data security intensive environments for AI inference. We believe this LOI represents a meaningful validation of LT350's potential to deliver secure, high-performance, on-premise inference compute directly adjacent to clinical operations."
LT350 estimates that approximately 18 months of design, engineering, and testing work will be required following the closing of the proposed merger between Auddia and Thramann Holdings, LLC to stand up the first canopy. Because LT350 represents a new class of distributed AI infrastructure, the company believes this timeline reflects the rigor required to validate performance, safety, reliability, and compliance in a hospital environment.
If the pilot is successful, LT350 expects to expand across the medical REIT's broader portfolio of almost 200 medical properties. These properties include hospitals, outpatient facilities, and medical office buildings—locations where proximity, data sovereignty, and deterministic performance are critical for AI-driven clinical and operational workflows.
Under its proposed business model, LT350 anticipates entering into site-specific lease agreements with property owners for the use of parking-lot airspace and canopy infrastructure. This structure enables deployment without requiring land acquisition while providing property owners with a new revenue stream tied to AI infrastructure. The company believes this model aligns incentives and supports scalable deployment across large property portfolios.
While advancing the pilot, LT350 intends to pursue additional partnerships with healthcare systems, logistics operators, research campuses, and other organizations. The company believes that turning underutilized parking lots into solar-powered AI micro-datacenters represents a compelling opportunity for property owners, hyperscalers, and enterprise customers seeking secure, on-premise AI capabilities.
For more information about LT350, visit www.LT350.com.
