Insider Brief
- Sedai has raised $20 million in Series B funding to scale its AI-driven platform for autonomous cloud infrastructure management across major cloud providers.
- The company’s system has executed over 25 million autonomous actions in production, resulting in $5 million in annual savings, 22,000 engineering hours reclaimed, and zero incidents.
- With its patented AI agents and Decision Engine, Sedai automates smart scaling, self-healing, and optimization, and plans to expand into GPU and LLM-based workload management.
PRESS RELEASE — Sedai, the self-driving cloud™, announced today it has raised $20 million in Series B funding to bring autonomous operations to cloud infrastructure. The round was led by AVP (Atlantic Vantage Point), with participation from Norwest, Sierra Ventures, and Uncorrelated Ventures.
Sedai is defining a new category of AI agent–driven infrastructure automation, as enterprises move beyond dashboards and alerts to systems that act autonomously in production. As the first self-driving cloud, Sedai is a fundamental shift in how infrastructure is managed. Just as autonomous vehicles are replacing human drivers with intelligent systems trained on real-world data, Sedai replaces manual operations with AI agents that take safe, continuous action.
Already, Sedai has executed over 25 million autonomous actions in production, managing $1.2 billion in cloud spend across hundreds of thousands of cloud services. The result: More than $5 million in annual savings for enterprise customers, over 22,000 hours of engineering time reclaimed, and zero incidents — establishing Sedai as the most trusted AI system to safely manage critical cloud infrastructure at scale.
“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.”
Sedai connects directly with AWS, Microsoft Azure, and Google Cloud. Its patented AI agents learn each environment’s behavior and autonomously manage compute, storage, and traffic in real time. Customers can start by observing Sedai’s decisions and then gradually enable full automation as trust builds.
Core capabilities include:
● Smart Scaling: Uses deep reinforcement learning to dynamically allocate resources. Customers have seen up to 65% cost reduction on Kubernetes clusters and 28% on VM workloads through precise scaling.
● Self-Healing: Detects and resolves issues such as degradation and outages, before they impact users. While most tools rely on alerts or manual response, Sedai acts instantly to fix problems in production.
● Continuous Optimization: Makes continuous optimizations to infrastructure behind the scenes. Customers report 6X increases in operations productivity and 30% improvements in performance.
At the core of Sedai’s platform is its Decision Engine, which orchestrates multiple AI agents, each focused on different goals, such as cost, availability, or latency. The system adapts to changes in topology and traffic using a combination of seasonality modeling, anomaly detection, and causal inference. Sedai holds a portfolio of U.S. patents that protect its ability to take action in the cloud safely.
Sedai is trusted and deployed by industry leaders in cybersecurity, financial services, pharmaceuticals, AI, and education, including the number one cybersecurity provider, the top innovation bank, and a global pharmaceutical company. These organizations rely on Sedai to manage mission-critical production systems and high-complexity machine learning workloads.
“Sedai is a game-changing tool, both for our cloud strategy and for me personally,” said Matthew Duren, Vice President of Engineering at KnowBe4. “From a cost perspective, Sedai reduced our spend by up to 50% in production and by up to 87% in development, which meant it very quickly paid for itself. And 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.”
With the funding, Sedai will expand its platform and introduce several first-of-its-kind capabilities, including self-tuning for LLM-based applications, autonomous GPU optimization, and AI-powered orchestration for platforms such as Databricks and Snowflake. The company will also rapidly scale its go-to-market team, driven by new Chief Revenue Officer Vaneet Bhaskar.
“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, and we are honored to be part of the company.”
Sedai grew revenue 7X in 2024, fueled by large-scale deployments across multiple Fortune 500 firms and a 92% POC-to-customer conversion rate. With this round, the company is accelerating product innovation and go-to-market expansion.
“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.”
