The AI boom has fundamentally changed how startups think about infrastructure. What was once a relatively straightforward cloud scaling journey has become far more complex, as companies now balance GPU-intensive workloads, rapidly evolving AI models, compliance requirements, and rising operational costs. For many startups, the challenge is no longer simply getting a product to market. It is keeping cloud operations sustainable while scaling fast enough to compete.
At the same time, AWS has evolved into far more than a hosting platform. For startups building AI-native products, it has become an orchestration layer for everything from deployment pipelines to generative AI governance. According to Automat-it CEO Ziv Kashtan, the startups that scale most successfully are the ones that treat cloud architecture as a strategic advantage rather than an afterthought.
The Hidden Cost Of Scaling Too Fast
“Early on, we saw that rapidly growing startups often let their cloud spend outpace their revenue,” Kashtan says. That observation shaped Automat-it’s strong emphasis on continuous FinOps optimization as part of its AWS managed services approach.
The company, an AWS Premier Partner specializing in startups, has supported thousands of companies as they move from MVP to production. What began as a DevOps-focused business has evolved into an AI services company helping startups operationalize increasingly complex AI workflows on AWS.
