Railway, a San Francisco-based cloud platform that has quietly built a user base of two million developers without paid marketing, just closed a $100 million Series B funding round. The raise is significant not for its size alone—the cloud infrastructure space attracts capital constantly—but for what it represents: investor recognition that legacy cloud providers like AWS are architecturally unsuited for modern AI workloads. Railway's pitch centers on what it calls 'AI-native cloud infrastructure,' a category that didn't exist five years ago. Unlike AWS, which optimizes for general-purpose computing and was designed for stateless web applications, Railway rethinks infrastructure from the ground up for AI's specific demands: efficient GPU allocation, rapid iteration cycles for model training, automatic scaling for inference, and seamless integration with machine learning frameworks. The company claims this architectural alignment delivers faster deployment, lower infrastructure costs, and better resource utilization than retrofitting AI workflows onto legacy platforms.