Sedai Rakes in $20M to Expand the Self-Driving Cloud

Enterprises are spending billions managing infrastructure that still requires humans to respond to alerts and monitor performance. But what if the cloud could manage itself? Sedai, a San Francisco-based startup, is bringing that idea to fruition. With its recently announced $20 million Series B funding, Sedai is expanding what it calls “the world’s first self-driving cloud,” a patented AI platform that autonomously optimizes cloud environments to cut costs, improve reliability, and free up engineers to focus on building.. The stakes are high. Global cloud spending is expected to top $2 trillion by 2030, but up to 30% of that spend is wasted due to over-provisioning and inefficient scaling. Sedai’s AI-powered platform promises to fix that, claiming it currently manages over $3 billion in cloud spend and saves enterprise customers more than $5 million annually, all with zero incidents. “These aren’t projections. This is real AI, live in production,” said CEO and co-founder Suresh Mathew . “Just like Waymo proved that self-driving cars are possible, Sedai proves that self-driving infrastructure is not only possible, it’s necessary”. Mathew and co-founder Benjamin Thomas first confronted the limitations of cloud operations while leading engineering efforts at PayPal. As microservices exploded across the company’s architecture, they saw firsthand how DevOps, while enabling speed and scale, had also amplified operational burden. “Observability tools solved visibility but created alert fatigue,” Mathew said. “We needed something that could act, not just react”. The duo built a prototype that used AI/ML to detect performance degradation and autonomously remediate issues. It worked so well that they realized it was the seed for what would become Sedai. Autonomous Optimization at Scale Sedai’s platform uses a number of AI agents to manage compute, storage, and traffic across AWS, Azure, GCP, Kubernetes, and even modern workloads like Databricks and large language models. These agents continuously learn from historical usage, traffic patterns, and system topology, applying real-time optimizations without user intervention. “Sedai doesn’t just save money, it rewrites the physics of how engineering teams operate,” said Tim Guleri, Managing Partner at Sierra Ventures. “It’s the first AI system we’ve seen that turns cloud infrastructure into a competitive advantage, not a cost center”. ROI and Impact on Customers At KnowBe4, Vice President of Engineering Matthew Duren shared strong returns: “Sedai reduced our spend by up to 50% in production and 87% in development. It very quickly paid for itself… Sedai helped me become a key strategic leader at KnowBe4. It frees up our team to focus on more valuable projects”. Across its customer base, which includes HP, Experian, and McGraw Hill, Sedai says it has reclaimed over 22,000 hours of engineering time, with clients reporting 92% conversion from pilot to full deployment. AI as Strategic Infrastructure Sedai’s growth has come alongside a shift in how organizations view cloud infrastructure. No longer just a cost center, infrastructure is increasingly being seen as a path for competitive differentiation and autonomous systems like Sedai are enabling that transition. The recent funding round, led by Atlantic Vantage Point with participation from Norwest, Sierra Ventures, and Uncorrelated Ventures, will help Sedai accelerate its roadmap. That includes expanding its AI capabilities to optimize GPU clusters and LLM-based applications, as well as supporting orchestration for platforms like Databricks and Snowflake. "AI is the only safe and efficient way to solve this problem at scale," said Mathew. “That’s why we built the first autonomous cloud management platform that can safely optimize everything from Kubernetes to Databricks, so engineers can focus on innovating with data, not micromanaging their clusters”. The basis of Sedai’s mission is to improve the lives of engineers. “We will not rest until we see engineers operate the IQ tasks and Sedai operates the mundane AI tasks on their behalf,” the company declares on its website. As Mathew puts it, “We built Sedai to let every engineer experience the same benefits of an autonomous system that has previously only been accessible to the large enterprise technology companies”.

Sedai Rakes in $20M to Expand the Self-Driving Cloud

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