Can AI data centers be mass-produced like cars? This startup aims to find out

AI infrastructure company Runware is making news again, just months after unveiling the Sonic Inference Pod, a modular data center built in a factory and shipped to customers ready to install. Now the company has bigger plans. It told TechCrunch it wants to build a factory that assembles these pods on a production line, as if they were cars.

The idea isn’t entirely new. Companies like Crusoe and Schneider Electric also sell prefabricated pods, but Runware says it can ship its pods faster. 

Flaviu Radulescu, co-founder and CEO of Runware, told TechCrunch that the company plans to scale production at its Romania-based factory to 30 megawatts of data center capacity per day by 2028, or nearly 1 gigawatt per month. That’s a whole lot of capacity: at that pace, Runware would produce roughly as much in a year as the entire U.S. was expected to add in data center power this year, about 10 gigawatts. But it also reflects an industry-wide push to deploy data centers faster more efficiently. 

Nvidia announced, for example, the Vera Rubin AI factories and the DSX POD earlier this year. Both are also meant to make it faster and easier for companies to build their own AI data centers. The difference with Runware, though, is that it says it has actually built a factory rather than just designed the infrastructure that would let others build one. 

Radulescu said Runware will gradually increase production starting next year and that it already has two factories — one it has used for a few years to build the pods, and a second it started building earlier this year. The second is expected to be finished within months and go online early next year. 

Runware will manufacture the modular data centers on an assembly line. Customers can provide their own site to assemble them, or Runware can find one for them. Radulescu said Runware aims to bring the pods online within 48 hours. That time covers installation and set-up time, not build time. A pod once took three weeks to build but it will soon take one day as it ramps up production, says the company. Runware will provide spare parts if components fail. Customers can also rent compute from Runware or supply their own GPUs and pay a monthly fee for the pods and operations. Power and internet are charged separately, he said. 

The pods can also be customized to customer preferences, he said. The pods have a standard design, but can be configured to meet customer requirements and the latest GPU chips. Chips can take a long time to arrive after they’re ordered, which works in Runware’s favor. “Our pod delivery times are also shorter than current GPU lead times, giving us time to adapt the infrastructure to the hardware being ordered,” he said. “For new GPU generations, our in-house hardware team can design, build, and test components itself, allowing us to adapt quickly.” 

Right now, these are all plans — execution is the test. The factory will need a lot of people, inventory, supply chain logistics, and money. There are cautionary tales about reinventing manufacturing, notably the electric vehicle startup Arrival, once valued at over $13 billion, which struggled to mass-produce electric vehicles cost-effectively compared with traditional plants. Runware, which has raised more than $60 million to date, said it plans to raise a Series B, but for now it is finishing and launching the factory with the $50 million Series A it raised last December.

“Our cost structure is very different,” Radulescu said, explaining how Runware seeks to avoid Arrival’s fate. “We do have headcount and materials cost,” he continued. “But our factory staff is cost-effective relative to the value of deploying compute for AI.” He also said that designing its own systems and buying widely available, affordable parts helps keep costs low. “We’ve brought in a highly experienced plant manager from the automotive industry to work alongside our chief of hardware and help us get that execution right.”

Sourcing components could also be a challenge. Though Runware says it designs and builds its own cooling and other pod systems with standard components, some parts, such as pumps and fans, come from Germany, and it still depends on Nvidia for networking. Still, Runware claims it has received $1 billion in committed interest for its Sonic pods since it began offering them to outside customers a month ago, “representing over 20 megawatts, which we’re now working to deliver,” Radulescu said.

Data centers in the U.S. and abroad have come under fire for how much energy they consume and how that affects the grid and other resources. When pressed, Radulescu said his company’s pods only need power and an internet connection. They’ll use a closed-loop liquid cooling system with air-cooled radiators to release heat, so they don’t really need a water connection. “We’re working with power providers on a site pipeline covering 397 megawatts, with potential to expand to 1.2 gigawatts,” he said, referring to its list of planned sites and adding that the company is deploying its modular data centers on sites that are much smaller than those used by hyperscalers like Amazon, Microsoft, and Google.

The sites, he continued, typically already have power, so they shouldn’t further strain the grid or disrupt the community. The pods also run “completely silent up to temperatures of 86 degrees Fahrenheit. We use energy from renewable sources whenever possible,” he continued. “We are actively working on expanding our network of energy providers and sites. We’re aiming to have renewables as our main energy source.”

Next, Runware will bring its new factory online early next year, then expand to the U.S. and other regions worldwide. Modular systems are the future and will soon become “the standard for large AI deployment,” Radulescu said.

“Customers should be able to plan a hyperscale data center around factory-built pods from the beginning and have it working in months instead of years,” he added.