Auddia Inc. (NASDAQ: AUUD) today highlighted newly available market data that underscores the scale of the AI opportunity for LT350, a distributed AI infrastructure subsidiary of McCarthy Finney. The disclosure follows a recent SEC filing by SharonAI Holdings Inc. (NASDAQ: SHAZ), which announced a $1.25 billion, 60-month contract to deploy and operate 8,200 NVIDIA B300 GPUs for a global cloud customer. According to reports on the publicly filed agreement, the contract value equates to approximately $30,488 per GPU per year.
Auddia is using this publicly available benchmark to help investors contextualize the potential scale of LT350’s distributed AI infrastructure model relative to a previously disclosed internal DCF analysis of $250M for McCarthy Finney, fifty percent of which is attributed to LT350. This new additional market pricing datapoint may signify that LT350’s market opportunity may be larger than initially contemplated. LT350 is one of three new businesses that will be combined with Auddia in the new McCarthy Finney holding company if Auddia’s recently announced business combination with Thramann Holdings, LLC is completed.
“We are not providing forecasts or forward revenue projections outside of what is disclosed in our recent S-4 financing,” said Jeff Thramann, CEO of Auddia and Founder of LT350. “But I believe publicly disclosed market pricing helps investors understand why distributed AI infrastructure is emerging as one of the most compelling opportunities in the sector. Our business model is very similar to that of SHAZ with the added advantage of optimizing data sovereignty and latency by placing our proprietary datacenters directly next to the defense, healthcare, financial services, and government customers who need to optimize both data security and speed.”
LT350’s REIT partner controls 4,000,000 square feet of suitable parking-lot airspace. LT350’s patented canopy architecture is designed around 2,000-square-foot modules, each capable of supporting 480 GPUs using LT350’s 2:1 GPU-to-battery cartridge ratio. If fully deployed across the REIT footprint, LT350’s architecture could support approximately 2,000 canopies, 480 GPUs per canopy, and 960,000 GPUs total capacity. Using the publicly disclosed benchmark implying revenue of approximately $30,488 per GPU per year, this footprint would represent $29 billion in annualized market-equivalent pricing. Auddia emphasizes that actual pricing, utilization, and deployment levels will vary and that the company applies significant discounts in its internal DCF analyses.
While the REIT partnership provides a clear example of LT350’s potential scale, the canopy architecture is designed for broad applicability across multiple industries and property types, including hospitals, universities, retail centers, convenience stores, industrial facilities, municipal properties, stadiums, and multifamily housing. LT350’s patented design enables deployment in existing parking lot airspace, closed loop liquid cooling with zero water consumption, battery buffered operation for grid support, circuit level grid deployment without transmission upgrades, modular scaling from a single canopy to thousands, and distributed mesh connectivity with hyperscaler interoperability.
“The REIT footprint is just one example of how LT350 can scale,” Thramann added. “Our IP portfolio gives us a proprietary position in a category that is only beginning to emerge. The math is the math and when investors contemplate the IP and innovation inherent in the LT350 platform, they will understand why we believe LT350 represents a rare and highly defensible opportunity.”
For information about LT350, please visit www.LT350.com. LT350’s whitepaper, “Distributed, Power-Sovereign AI Infrastructure for the Inference Economy,” is available here.
