Auddia’s LT350 Business Proposes Distributed AI Infrastructure Using Parking Lot Canopies

Auddia Inc. has provided a strategic overview of its LT350 distributed AI compute business, which the company describes as a core asset in its proposed merger with Thramann Holdings. The LT350 platform represents a novel approach to AI infrastructure, designed to deploy small, interconnected data centers within the ceiling space of proprietary solar parking lot canopies without consuming parking spaces.

The technology, protected by 13 issued and 3 pending patents, is engineered to address two critical constraints in the AI market: GPU underutilization and grid-constrained data center deployment. Jeff Thramann, CEO of Auddia and founder of LT350, stated the business aims to build the distributed inference layer for AI, which he believes will be faster to deploy, cheaper to operate, and more energy efficient than traditional models. The architecture integrates modular GPU, memory, and battery cartridges directly into the canopy structure, transforming the airspace above parking lots into revenue-generating AI compute centers optimized for inference tasks.

LT350 is purpose-built for the shift in AI workloads from centralized training to real-time, distributed inference. The company believes this creates demand for compute that is physically close to data sources, less dependent on strained electrical grids, faster to deploy, and aligned with data sovereignty requirements. By deploying in parking lots adjacent to key facilities, LT350 aims to serve latency-sensitive and regulated workloads. Target verticals include hospitals and health systems requiring HIPAA-aligned inference, financial institutions needing low-latency execution, and defense organizations with strict isolation requirements. For more information about LT350, please visit https://www.LT350.com.

The power-sovereign architecture integrates solar generation and battery storage into each canopy, enabling behind-the-meter power buffering, peak-shaving, and reduced grid interconnection requirements. This design is intended to help the platform scale amid growing grid constraints faced by utilities and hyperscalers. Deployment in existing parking lots offers structural advantages, including zero land acquisition costs, no loss of parking functionality, and faster permitting processes compared to traditional data centers.

Auddia believes LT350 delivers a different economic model for inference infrastructure by combining modular GPU deployment with solar-plus-storage energy systems. The company anticipates higher utilization by matching GPU deployment to inference needs, higher revenue from premium inference services, and lower energy costs from solar generation. The LT350 business accounts for approximately 50% of McCarthy Finney’s $250 million discounted cash flow valuation. The proposed merger would combine LT350 with Auddia’s existing audio AI platform under the new holding company. Investors can find additional information through the SEC’s website at https://www.sec.gov.

This news story relied on content distributed by PRISM Mediawire. Blockchain Registration, Verification & Enhancement provided by NewsRamp. The source URL for this press release is Auddia’s LT350 Business Proposes Distributed AI Infrastructure Using Parking Lot Canopies.

The post Auddia’s LT350 Business Proposes Distributed AI Infrastructure Using Parking Lot Canopies appeared first on citybuzz.