Runware, an AI infrastructure company, is back in the spotlight just months after introducing the Sonic Inference Pod—a modular data center manufactured in a factory and delivered to customers ready for installation. Now the company has even bigger ambitions.

The concept itself isn't novel. Companies such as Crusoe and Schneider Electric also offer prefabricated pods, but Runware claims it can deliver its units faster. The scale of this capacity is striking: at its projected 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—approximately 10 gigawatts. This also mirrors a broader industry trend toward deploying data centers more quickly and efficiently. Nvidia, for instance, announced its Vera Rubin AI factories and the DSX POD earlier this year, both designed to make it faster and easier for companies to build their own AI data centers. What sets Runware apart, however, is that it says it has actually constructed a factory rather than merely designing infrastructure that would enable others to build one.

Fadulescu explained that Runware will gradually ramp up production starting next year and already operates two factories—one it has used for several years to build the pods, and a second it began constructing earlier this year. The second facility is expected to be completed within months and operational early next year. Runware will manufacture the modular data centers on an assembly line. Customers can provide their own site for assembly, or Runware can locate one for them. Fadulescu said Runware aims to bring the pods online within 48 hours—a timeframe that covers installation and setup, not build time. A pod once took three weeks to build, but the company says it will soon take just one day as production scales up. Runware will supply 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, with power and internet charged separately. The pods can be customized to customer preferences, Fadulescu noted. While they have a standard design, they can be configured to meet specific requirements and accommodate the latest GPU chips. Chips often take a long time to arrive after being ordered, which actually 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 will be the real test. The factory will require substantial staffing, inventory, supply chain logistics, and capital. 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 completing and launching the factory with the $50 million Series A it raised last December. "Our cost structure is very different," Fadulescu 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 noted that designing its own systems and purchasing 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 present challenges. Although Runware says it designs and builds its own cooling and other pod systems using standard components, some parts—such as pumps and fans—come from Germany, and it still depends on Nvidia for networking. Nevertheless, 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," Fadulescu said. Data centers in the U.S. and abroad have faced criticism for their energy consumption and impact on the grid and other resources. When pressed, Fadulescu 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 require 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 much smaller than those used by hyperscalers like Amazon, Microsoft, and Google. These 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," Fadulescu 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.