Vertiv and NVIDIA Unveil Pre-Engineered AI Factory Approach Targeting 30% More Token Output in First Year; Polar Deploys at Norway Site

At NVIDIA GTC Berlin, Vertiv Holdings Co. and NVIDIA introduced an AI factory approach that combines rapid configuration and virtual validation of pre-engineered reference architectures with factory-built deployment, designed to move AI facilities from project kickoff to productive capacity significantly faster. Under defined modeled assumptions, the approach can generate up to 30% more cumulative token output within the first 12 months using the same installed capacity, according to the companies. Polar Data Centers is already applying the factory-built deployment model to the first 41 MW phase of its multiphase AI data center at Herøya, Norway, a campus scalable to 100 MW.

The announcement addresses a critical bottleneck in AI infrastructure development. Securing compute is only part of the challenge for AI factory operators; traditional infrastructure development often requires power, cooling and facility systems to be engineered and integrated through separate, sequential processes, creating complexity and potential delays. The Vertiv and NVIDIA approach instead begins with pre-engineered AI factory reference architectures that can be rapidly configured to customer and site requirements, virtually validated before deployment, and then translated into factory-built infrastructure. The approach combines the NVIDIA Vera Rubin DSX AI Factory reference design and NVIDIA Omniverse DSX Blueprint with Vertiv SimReady power and cooling assets, integrated with Dassault Systèmes' 3DEXPERIENCE agentic platform.

The configuration and validation stage delivers substantial time savings. Rather than developing an integrated infrastructure design from scratch, teams can configure and virtually validate proven reference designs against project requirements, interfaces and constraints in a shared virtual environment. In the modeled scenario, this reduces the time from requirements to a configured and validated AI factory solution from approximately 30 days to three days, a tenfold improvement. Vertiv is also contributing SimReady OpenUSD assets of its power and cooling equipment to the SimReady Central Library on Hugging Face, helping engineering teams discover and reuse validated equipment assets in AI factory digital twins.

On the deployment side, Vertiv's prefabricated solutions shift more assembly, integration and testing into the factory before equipment reaches the site. These solutions include Vertiv OneCore, a hybrid-built data center solution integrating critical power, thermal management and supporting infrastructure, and Vertiv SmartRun, a prefabricated overhead infrastructure system for high-density power distribution, liquid cooling, networking and containment. In the modeled scenario, the factory-built approach reduces the infrastructure deployment period from approximately 90 days to 45 days, a reduction of up to 50%. Combined with the faster configuration and validation enabled by pre-engineered reference designs, the modeled approach reduces these stages from approximately 120 days to 48 days, making productive AI capacity available about 10 weeks sooner.

"An AI factory earns its return in tokens, and every day spent configuring infrastructure or integrating it on site is output that never comes back," said Giordano Albertazzi, CEO of Vertiv. "Success depends on how quickly operators can move from requirements to productive AI capacity. By starting with pre-engineered reference designs that can be rapidly configured and validated, then extending that approach through factory-built deployment, we help customers reduce complexity, deploy infrastructure faster and bring AI capacity online sooner. Polar Data Centers is demonstrating how that approach can be applied at scale in a real-world AI factory deployment."

At the Herøya campus, Vertiv is supplying prefabricated power and thermal modules, Vertiv SmartRun overhead infrastructure and Vertiv SmartMod, supported by Vertiv Unify software. "Our customers measure us on how quickly capacity is ready for them," said Andy Hayes, CEO of Polar Data Centers. "At Herøya, Vertiv's factory-built infrastructure helps us manage the complexity of deploying power, cooling and white-space systems for high-density computing. It gives us a more disciplined, repeatable deployment model while preserving the flexibility to meet the requirements of our customers."

The collaboration also drew commentary from NVIDIA and Dassault Systèmes. "AI factories must be designed as one system, and the NVIDIA Vera Rubin DSX AI Factory reference design helps teams align compute, power and cooling requirements from the outset," said Vladimir Troy, Vice President of AI Infrastructure at NVIDIA. "With the NVIDIA Omniverse DSX Blueprint, companies such as Vertiv and Dassault Systèmes can simulate these systems together and carry an integrated design into physical deployment, helping operators resolve conflicts earlier and bring productive AI capacity online sooner." Stéphane Sireau, Vice President, High-Tech Industry, at Dassault Systèmes, added: "With Vertiv and NVIDIA, we're accelerating AI factory design and deployment by engineering the factory as one system — compute, networking, power and cooling co-designed and co-simulated in a virtual twin. Integration issues get resolved before construction, not on site, helping bring token-producing capacity online sooner."

The industry implications extend beyond individual projects. As AI workloads scale and operators race to convert capital investment into productive compute, the ability to compress design and deployment timelines from months to weeks represents a meaningful competitive advantage. By treating the AI factory as a single integrated system — from virtual design through factory-built assembly — the Vertiv and NVIDIA approach aims to reduce the field complexity and sequential delays that have historically slowed high-density, liquid-cooled capacity from reaching customers. Vertiv and NVIDIA plan to demonstrate elements of the approach at NVIDIA GTC Berlin, including how facility requirements inform infrastructure configuration, how teams can virtually validate power and cooling requirements, and how factory-built infrastructure accelerates physical deployment.