Autonomous infrastructure management is no longer a theory—Sedai is putting AI agents in the driver’s seat of enterprise cloud ops.
The dream of a self-driving cloud just shifted into the fast lane. Sedai, a pioneer in autonomous cloud operations, announced today it has raised $20 million in Series B funding to scale its AI-driven infrastructure platform. The round, led by AVP (Atlantic Vantage Point) with participation from Norwest, Sierra Ventures, and Uncorrelated Ventures, underscores investor confidence in what could be the next generational leap in cloud computing.
Sedai isn’t just automating alerts or spinning up instances faster. It’s redefining how cloud environments are managed entirely—by handing over decision-making to AI agents trained to monitor, optimize, and act in real time. These agents, orchestrated by Sedai’s proprietary Decision Engine, quietly steer traffic, manage compute loads, and resolve incidents before they ever hit a dashboard.
“Just like Waymo proved that self-driving cars are possible, Sedai proves that self-driving infrastructure is not only possible, it’s necessary,” said Suresh Mathew, Sedai’s CEO and founder.
Unlike traditional monitoring or ops platforms that generate floods of alerts and depend on manual intervention, Sedai’s system is built to act. With more than 25 million autonomous decisions executed across cloud services like AWS, Azure, and Google Cloud, the company claims it has already managed $3 billion in cloud spend, saving enterprise customers over $5 million annually and reclaiming 22,000 engineering hours.
The approach is simple in concept, complex in execution: AI agents monitor infrastructure for anomalies, apply seasonality modeling and causal inference, and then make real-time changes—without needing a human in the loop. The result? Smart scaling with up to 65% cost reduction in Kubernetes environments, self-healing for degraded services, and continuous behind-the-scenes optimizations that improve performance by up to 30%.
“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.”
One enterprise that’s already seeing ROI is KnowBe4. “Sedai is a game-changing tool, both for our cloud strategy and for me personally,” said Matthew Duren, VP of Engineering. “From a cost perspective, Sedai reduced our spend by up to 50% in production and by up to 87% in development… It frees up our team to focus on more valuable projects.”
The company’s success in 2024—a reported 7X revenue growth and a 92% POC-to-customer conversion rate—has put it on the radar of organizations facing cloud chaos at scale. Its clients include major players in cybersecurity, pharmaceuticals, education, and AI, many running mission-critical and ML-intensive workloads that require reliability without compromise.
With its new funding, Sedai plans to double down on its roadmap. Next up: AI agents that autonomously optimize GPU workloads, tune infrastructure for large language model (LLM) performance, and orchestrate complex cloud environments across platforms like Snowflake and Databricks.
“As cloud adoption increases, companies are now struggling to improve the availability and performance of their infrastructure, while also reducing cost,” said Manish Agarwal, General Partner at AVP. “What enterprises really need is a way to optimize their cloud environment, in real time. Our view is that AI agents are uniquely positioned to address this need and enable autonomous cloud management. Sedai fits squarely into that thesis.”
Sedai’s vision may still sound futuristic to some, but in practice, it’s already here—and already acting. The age of DevOps dashboards and reactive fire drills is giving way to an era where systems fix themselves before humans even notice something was wrong.
Whether it becomes the de facto model for managing the modern cloud remains to be seen. But one thing is clear: Sedai is betting that tomorrow’s infrastructure won’t just be smarter. It’ll drive itself.
