Sedai, the autonomous cloud infrastructure provider, has secured $20 million in Series B funding to scale its AI-driven infrastructure automation, accelerate self-healing cloud systems, deliver greater cloud cost optimization, enhance self-driving DevOps, and expand smart scaling capabilities across enterprise cloud environments.

Led by Atlantic Vantage Point (AVP) with participation from Norwest, Sierra Ventures, and Uncorrelated Ventures, the latest funding round empowers Sedai to replace traditional reactive cloud operations with a proactive, intelligent solution. While most platforms focus on monitoring dashboards and alerts, Sedai advances AI-driven infrastructure automation to take autonomous actions in live production environments without human intervention.

Unlike conventional DevOps tools, Sedai embodies the essence of self-driving DevOps by enabling its AI agents to predict and act on infrastructure demands. Through continuous learning and decision-making, these agents dynamically manage cloud resources, applying smart scaling to optimize workloads and minimize overhead.

“These aren’t projections. This is real AI, live in production,” said Suresh Mathew, CEO and Founder of Sedai. “Just like Waymo proved that self-driving cars are possible, Sedai proves that self-driving infrastructure is not only possible, it’s necessary.”

The Engine Behind the Cloud That Runs Itself

At the core of Sedai’s autonomous cloud infrastructure lies a patented Decision Engine that orchestrates multiple AI agents. Each agent targets a specific operational goal, such as reducing latency, improving availability, or achieving cost savings. The system adapts autonomously to fluctuations in traffic and changes in topology, executing safe and efficient actions across computing, storage, and networking components.

Through seamless integration with AWS, Microsoft Azure, and Google Cloud, Sedai’s AI agents enhance AI-driven infrastructure automation by learning the behavioral patterns of each environment. This enables self-healing cloud systems to detect degradation and outages early. It also resolves them before users ever notice a problem.

“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 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, and we are honored to be part of the company,” added Manish.

Real-World Impact: Billions in Spend, Millions in Savings

Sedai’s platform has already executed more than 25 million autonomous actions in live production settings, managing $3 billion in cloud spend. This initiative has delivered measurable results, including over $5 million in annual customer savings, more than 22,000 engineering hours reclaimed, and zero production incidents. These achievements are powered by deep cloud cost optimization strategies driven by automation.

Clients across industries, including cybersecurity, pharmaceuticals, finance, and education, use Sedai’s self-driving DevOps tools to manage their most mission-critical systems. Whether tuning AI/ML workloads or scaling real-time applications, Sedai ensures operational excellence without manual oversight.

“Sedai is a game-changing tool, both for our cloud strategy and for me,” said Matthew Duren, Vice President of Engineering at KnowBe4.

“From a cost perspective, Sedai reduced our spending by up to 50 percent in production and by up to 87 percent in development, which meant it very quickly paid for itself. From a personal perspective, Sedai helped me become a key strategic leader at KnowBe4. It frees up our team to focus on more valuable projects,” added Matthew.

Smart Scaling that Thinks Ahead

One of Sedai’s standout features is smart scaling, which utilizes reinforcement learning to optimize infrastructure in real time. Customers have reported up to 65 percent cost reduction on Kubernetes clusters and a 28 percent decrease in virtual machine overhead, all while maintaining or improving performance.

This capability directly ties into Sedai’s broader strategy for autonomous cloud infrastructure, where systems not only scale up or down as needed but also make intelligent decisions about when and how to do so. These choices are not static but evolve based on environmental variables, usage patterns, and historical data, improving both efficiency and resilience.

Sedai’s roadmap is just as ambitious as its current success. The company plans to introduce self-tuning capabilities for LLM-based applications, autonomous GPU optimization, and deeper integrations with data platforms such as Databricks and Snowflake. These enhancements will further strengthen its AI-driven infrastructure automation toolkit, unlocking new levels of performance.

To support this expansion, Sedai has appointed Vaneet Bhaskar as Chief Revenue Officer and will scale its global go-to-market team. This aligns with the company’s significant growth in 2024 when it saw a 7X revenue increase and achieved a 92% conversion rate from proof of concept to full deployment.

Why Enterprises Are Betting on Sedai

Today’s enterprises demand agility, reliability, and efficiency. Sedai answers that call with its combination of autonomous cloud infrastructure, self-healing cloud systems, and smart scaling, proven across real-world deployments.

By eliminating manual operations, enabling true self-driving DevOps, and delivering unparalleled cloud cost optimization, Sedai empowers engineering teams to focus on innovation rather than routine maintenance. In doing so, it redefines what’s possible in modern cloud management.

“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.”

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