RESS RELEASE: EPRI today announced a collaboration with Prologis, NVIDIA, and InfraPartners to study smaller-scale data centers designed for distributed inference, a form of real-time data processing used across sectors including logistics, health care, finance, and public services. The announcement was made today at DTECH.
The collaborators will assess the deployment of micro data centers—ranging from 5 to 20 megawatts—at or near utility substations with available grid capacity that can be quickly set up. The goal is to bring inference capabilities—the process of generating real-time responses from trained models—closer to where data is generated and consumed, while making better use of underutilized infrastructure and reducing pressure on congested transmission systems.
The companies will explore how smaller, distributed sites can meet computing needs without straining the grid. The collaboration aims to have at least five pilot sites in development across the U.S. by the end of 2026, providing a replicable model for rapid, scalable deployment.
“AI is transforming every industry, and the energy system will need to continue to evolve to meet increasing demand,” said EPRI President and CEO Arshad Mansoor. “This collaboration with Prologis, NVIDIA, InfraPartners, and the utility community highlights the type of innovative actions required to meet the moment. Using existing grid capacity to bring inference compute closer to where it’s needed—quickly and reliably—is a win for all.”
As artificial intelligence applications scale across industries, demand for AI inference continues to surge. Meeting this demand not only requires more compute, but AI infrastructure deployed closer to end-users to relieve pressure on congested transmission systems.
From autonomous logistics to fraud detection and digital diagnostics, inference systems are playing an increasingly important role in supporting real-time decision-making across nearly every sector of the economy. These workloads don’t require hyperscale facilities, but they do demand reliable, fast, and location-sensitive compute power. By moving inference closer to the edge of the grid, utilities and infrastructure providers can respond more efficiently to the growing volume and velocity of data.
This approach also supports grid reliability. By co-locating computing capacity with substations that have existing but underused distribution headroom, utilities may reduce transmission congestion, improve system flexibility, and help integrate renewable energy.
“As energy demand grows, we need infrastructure solutions that support grid reliability and make better use of what’s already built,” said Parag Soni, senior vice president and global head of Utility Strategy and Engagement at Prologis. “This collaboration is about using our development and energy expertise to help deliver smarter, more flexible infrastructure right where it’s needed.”
“AI is driving a new industrial revolution that demands a fundamental rethinking of data center infrastructure,” said Marc Spieler, senior managing director for the Global Energy Industry at NVIDIA. “By deploying accelerated computing resources directly adjacent to available grid capacity, we can unlock stranded power to scale AI inference efficiently. This distributed approach, powered by NVIDIA accelerated computing, maximizes existing energy assets, helping to deliver the intelligence required to transform every industry.”
Each organization will play a key role in supporting this project and the development of sites that relieve pressure on the grid:
- EPRI, independent, non-profit R&D institute: Provides independent, unbiased technical expertise and research-based validation. The institute identifies and supports locations that have capacity and fiber connections for joint demonstrations. EPRI also collects lessons learned, analyzes results, and confirms how well active projects perform so future distributed inference projects can follow best practices.
- Prologis: Identifies and evaluates suitable land and buildings near substations for rapid deployment, and coordinates development, planning, permitting, and delivery as demonstration sites advance. Will lead the long-term commercialization approach for this partnership. Prologis’ experience supporting energy and infrastructure deployment across its portfolio helps enable earlier site readiness as locations are evaluated.
- NVIDIA: Delivers optimized, GPU-accelerated computing platform for distributed inference workloads, offers technical guidance on distributed inference architectures, and facilitates connections to potential compute offtakers.
- InfraPartners, AI data center builder: Provides AI data centers designed for high-density power and cooling, and built using advanced offsite manufacturing.
- Participating utilities: assesses available distribution capacity; informs siting and interconnection pathways; and ensures alignment with operational requirements.
“AI is becoming the real-time engine of growth for the modern economy, and it demands a new kind of digital infrastructure,” said Harqs Singh, chief technology officer at InfraPartners. “By pairing InfraPartners’ AI data center solutions with EPRI’s technical leadership, NVIDIA’s platforms, and Prologis’ national footprint, we’re enabling rapid deployment of AI nodes where they’re needed most. Together, we’re building the foundation for the next decade of intelligent infrastructure.”
Contact:
Rachel Gantz
Senior Manager of Corporate Media Relations
202-293-7517
rgantz@epri.com
About EPRI
Founded in 1972, EPRI is the world’s preeminent independent, non-profit energy research and development organization, with offices around the world. EPRI’s trusted experts collaborate with more than 450 companies in 45 countries, driving innovation to ensure the public has clean, safe, reliable, and affordable access to electricity across the globe. Together…shaping the future of energy.®
Contact Info
Rachel Gantz
rgantz@epri.com
+1 202-293-7517
