Railway’s $100M bet: Building an AI-native cloud from scratch

Railway, the San Francisco cloud startup that’s been flying under the radar with two million developers and zero marketing spend, just dropped a bombshell: $100 million in Series B funding. The round, led by TQ Ventures with FPV Ventures, Redpoint, and Unusual Ventures hopping on, values the company as one of the most interesting infrastructure plays to come out of the AI boom.

And honestly? The numbers back it up. Railway processes over 10 million deployments per month and handles more than one trillion requests through its edge network. That’s the kind of scale you’d expect from a company with ten times the headcount and a much bigger war chest.

The core insight here is painfully simple: the tools developers use to deploy and manage software were designed for a world where code took hours or days to write. Now AI coding assistants like Claude, ChatGPT, and Cursor can churn out working code in seconds. But deploying that code? Still takes two to three minutes if you’re using Terraform and the old guard’s infrastructure.

“When godly intelligence is on tap and can solve any problem in three seconds, those amalgamations of systems become bottlenecks,” said Jake Cooper, Railway’s 28-year-old founder and CEO. He’s not wrong. A three-minute deploy time was fine when you spent an hour writing the code. Now it’s the slowest part of the loop.

Railway claims its platform delivers deployments in under one second. That’s fast enough to keep pace with AI-generated code, and customers are reporting real results: tenfold increases in developer velocity and up to 65 percent cost savings compared to traditional cloud providers.

Daniel Lobaton, CTO at G2X, a platform serving 100,000 federal contractors, saw his deployment speeds jump seven times faster and his infrastructure bill drop from $15,000 per month to around $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.

Here’s where Railway gets really interesting. In 2024, the company made the unusual decision to abandon Google Cloud entirely and build its own data centers. That’s a bold move for a startup with only 30 employees, but it echoes the Alan Kay philosophy: “People who are really serious about software should make their own hardware.”

Cooper explained the reasoning: “We wanted to design hardware in a way where we could build a differentiated experience. Having full control over the network, compute, and storage layers lets us do really fast build and deploy loops, the kind that allows us to move at ‘agentic speed’ while staying 100 percent the smoothest ride in town.”

This vertical integration paid off during recent widespread outages that hit major cloud providers. Railway stayed online throughout. And it enables pricing that undercuts the hyperscalers by roughly 50 percent and newer cloud startups by three to four times.

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 virtual machines. That’s a direct attack on the traditional cloud model 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 raised only $24 million before this round, including a $20 million Series A from Redpoint in 2022. Now they’re sitting on $100 million with a valuation that puts them squarely in the conversation as a serious infrastructure contender.

Is Railway going to kill AWS? Probably not anytime soon. But they’re carving out a real niche for developers who need speed and cost efficiency in the AI era. And with two million developers already on board without spending a dime on marketing, word of mouth is doing just fine.