Data Centres

Schneider Electric, Nvidia extend data centre partnership to scale AI Factories

17 March 2026
4 minutes
Schneider Electric is working with Nvidia to develop validated blueprints to design, simulate, build, operate and maintain gigawatt-scale AI Factories.
Image courtesy of Schneider Electric
Image courtesy of Schneider Electric

Announced during Nvidia GTC in San Jose, the partnership includes a new Nvidia Vera Rubin reference design that validates power and cooling for the latest Nvidia rack-scale architectures. This is in addition to the integration of advanced digital twin capabilities within the Nvidia Omniverse DSX Blueprint and ecosystem, alongside early testing of agentic AI for data centre alarm management services using NVIDIA Nemotron open models.

Building on an existing partnership, Nvidia and Schneider Electric said the collaboration aims to establish a comprehensive foundation for developing AI Factories built for gigawatt-scale and efficiency.

“Gigawatt-scale AI factories demand a fundamentally new class of energy-efficient and highly predictable infrastructure,” said Vladimir Troy, vice president of AI infrastructure at Nvidia. “Together, Nvidia and Schneider Electric are providing the power, cooling and digital twin architectures needed to accelerate time-to-token for our customers worldwide.”

The new Vera Rubin reference design is one of the first created for the Nvidia Vera Rubin NVL72 racks – covering power and cooling, in addition to being integrated with Schneider Electric’s controls reference designs.

It aims to address important infrastructure requirements and considerations for Nvidia’s latest rack-scale systems. This includes enabling new power distribution with increased supply voltage of 480 VAC, allowing higher TCS loop supply temperature of 45 degrees for improved efficiency. It also supports new IT room architecture with clusters of AI racks sharing centralised networking, storage, CPU and support racks.

Notably, it also seeks to maximise token performance by designing data centres to accommodate various operating points of GPU racks.

AVEVA, a leader in industrial software owned by Schneider Electric, is launching a new lifecycle digital twin architecture together with Nvidia that is designed to maximise GPU efficiency. With a goal to accelerate the deployment of AI Factories at speed and scale, Schneider Electric said it will create SimReady assets and digital twins through Nvidia Omniverse, supported by AVEVA’s advanced software.

AVEVA’s engineering and operations software is now embedded throughout the Nvidia Omniverse DSX Blueprint and ecosystem. The companies said it is projected to accelerate time-to-token through domain-specific simulations, digital visualisation and collaborative design tools that will drive significant engineering optimisation.

“As AI workloads scale in both size and complexity, the margin for error in data centre design becomes incredibly small,” said Manish Kumar, executive vice president, secure power & data centers at Schneider Electric. “Delivering AI at scale requires tightly integrated electrical, cooling and digital architectures that can support both unprecedented performance demands while maintaining peak energy efficiency.”

Schneider Electric announced a new reference design to support Nvidia Mission Control and Nvidia GB300 NVL72 back in September 2025, which included its ETAP and EcoStruxure IT design CFD models. These enable users to harness digital twins to simulate specific power and cooling scenarios.

Likewise, the company announced in October it would be supporting the transition to 800 VDC power architectures, led by Nvidia. These architectures are a critical requirement for emerging high-density rack systems being adopted across next-generation data centres.

Kumar added: “By combining advanced software, digital twins and validated reference designs, operators can simulate and optimise infrastructure before a single rack is deployed. This approach reduces risk, accelerates deployment and ensures the efficiency and resilience needed to power the next generation of AI Factories.”

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