Utilidata raises $60m to scale AI in energy infrastructure

  • May 6, 2025
  • Steve Rogerson

Rhode Island firm Utilidata has raised $60.3m to scale distributed AI across the energy infrastructure.

This series C funding will help Utilidata rapidly scale Karman, its distributed AI platform developed with Nvidia over the past four years. Built on a custom Nvidia module based on the Jetson Orin Nano edge AI platform, Karman can be embedded in any device connected to the energy system.

Rapid growth in data centre power demand alone is creating new constraints for grid operators and hyperscalers. By 2030, it is estimated that data centre power demand will increase 160 per cent. This growth combined with the global clean energy transition is creating increased complexity on the grid, requiring new and advanced options such as edge AI. By enabling high power compute and AI capabilities to be embedded directly into grid infrastructure and data centres, Karman can unlock grid capacity, increase reliability and reduce carbon emissions.

The Karman platform is available for purchase directly from Taiwanese IoT firm Advantech (www.advantech.com), making it easier for hardware partners to embed Karman into their equipment. Hubbell (www.hubbell.com) is already working with Utilidata to embed Karman into smart meters for electric utilities.

Utilidata’s partnerships are designed to support utilities through every phase of implementing edge AI at scale. The company announced last year a collaboration with Deloitte to support clients in navigating the modern power grid and has now partnered with Quanta Services to support the deployment of AI-enabled infrastructure at scale.

“Quanta’s expertise in electric infrastructure deployment positions us to help Utilidata scale AI across the grid,” said Andrew Schwaitzberg, senior vice president at Quanta Services (quantaservices.com). “We look forward to showcasing the power of edge AI at the Quanta Advanced Training Center, and working with our customers and partners to modernise infrastructure. By enabling AI onto the physical grid, we can continue to support infrastructure that is more reliable and resilient as our customers’ needs grow.”

The funding round was led by Renown Capital Partners, with participation from Quanta, Nvidia and existing investor Keyframe Capital. Citigroup acted as sole placement agent to Utilidata on the transaction.

“With this round of financing, Utilidata is positioned to deliver a major breakthrough in how the world manages power across the entire energy ecosystem,” said James McIntyre, managing partner at Renown Capital. “By bringing artificial intelligence to the edge of the grid, Utilidata’s Karman platform will help deliver unprecedented efficiency, resilience and security to energy infrastructure across the world.”

John Rapaport, CIO of Keyframe Capital, added: “By embedding AI and accelerated computing at the grid’s edge, Utilidata is unlocking critical insights and enabling utilities and industries to make smarter, more informed decisions. These new capabilities, which don’t exist today, will allow the energy industry to do more with existing infrastructure, tapping into valuable capacity on the grid at a time when load is growing rapidly for the first time in decades.”

These investments, which will help scale Karman (utilidata.com/meet-karman), come as several megatrends converge, including the rise of data centres and growing power demand. Quanta Services (quantaservices.com) brings expertise in deploying power grid infrastructure and will play a role in ensuring grid modernisation keeps pace with growing demands. AI innovations from Nvidia (www.nvidia.com) should help advance the transformative potential of Karman at the grid edge.

“Electricity has gone from being abundant and predictable to scarce and increasingly unpredictable,” said Josh Brumberger, CEO of Utilidata (utilidata.com). “That paradigm shift requires fundamentally new technology and deeper industry collaboration. We’re bringing together a powerful coalition of partners who are committed to scaling AI across the grid to build a modern and dynamic energy system.”