Railway, the San Francisco cloud platform that somehow got two million developers without spending a dime on marketing, just announced a $100 million Series B. TQ Ventures led the round, with FPV Ventures, Redpoint, and Unusual Ventures joining in.
The timing makes sense. Everyone is scrambling to run AI applications, and legacy cloud infrastructure is showing its age. AWS and Google Cloud weren’t built for the pace AI coding assistants demand.
Jake Cooper, Railway’s 28-year-old founder and CEO, put it bluntly in an interview: “As AI models get better at writing code, more and more people are asking the age-old question: where, and how, do I run my applications?”
He’s not wrong. The old cloud primitives are slow and outdated. When AI can generate working code in seconds, waiting two to three minutes for a deploy cycle is absurd.
Railway claims its platform delivers deployments in under a second. That’s fast enough to keep up with AI-generated code. Customers report a tenfold increase in developer velocity and up to 65 percent cost savings compared to traditional providers.
Those aren’t internal benchmarks either. Daniel Lobaton, CTO at G2X, saw deployment speeds improve by seven times and his infrastructure bill drop from $15,000 per month to roughly $1,000. “The work that used to take me a week on our previous infrastructure, I can do in Railway in like a day,” he said.
What makes Railway different from competitors like Render and Fly.io is how deep they go. In 2024, they abandoned Google Cloud entirely and started building their own data centers. That’s a bold move, but it lets them control the full stack.
“We wanted to design hardware in a way where we could build a differentiated experience,” Cooper said. Full control over network, compute, and storage means they can optimize for speed and density.
It paid off during recent cloud outages too. While major providers went down, Railway stayed online.
Pricing is aggressive. Railway charges by the second for actual compute usage: $0.00000386 per gigabyte-second of memory, $0.00000772 per vCPU-second, and $0.00000006 per gigabyte-second of storage. No charges for idle VMs. Compare that to traditional cloud where you pay for provisioned capacity whether you use it or not.
“The conventional wisdom is that the big guys have economies of scale to offer better pricing,” Cooper noted. “But when they’re charging for VMs that usually sit idle in the cloud, and we’ve purpose-built everything to fit much more density on these machines, you have a big opportunity.”
The company now processes more than 10 million deployments monthly and handles over one trillion requests through its edge network. That’s impressive for a startup that raised only $24 million before this round.
They’re running lean too. Thirty employees built a platform generating tens of millions in annual revenue. That’s the kind of efficiency you don’t see often.
Railway’s approach is a direct challenge to the hyperscalers. If they can keep delivering sub-second deployments, AI-native pricing, and better reliability, they might just carve out a real slice of the cloud market. The $100 million gives them room to scale up their data center buildout and go after bigger enterprise deals.
I’ve seen plenty of “AWS killers” come and go. But Railway’s traction — two million developers with zero marketing spend — suggests they’re onto something real. The AI boom is creating new demands that old infrastructure wasn’t designed for. Railway is betting that matters.
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