Trusted by leading enterprises (HP, Expedia, Palo Alto Networks, and more) to cut cloud costs by up to 65% using patented, real-time AI, while improving performance and reliability.
Unlike Kubecost, our AI is patented to safely eliminate your wasted spend. That's why industry leaders trust Sedai with their critical infrastructure.
Trusted by industry leaders
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Cost, Performance & Availability — not just cost
K8s, VMs, ECS, Lambda, S3, RDS, and more
Autonomous AI with built-in guardrails
CoPilot or AutoPilot — you stay in control
Out-of-the-box integration in minutes
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Sedai has helped us save millions of dollars by optimizing and managing our own back-end services. But most importantly, what Sedai has done very well is allow us to respond in real time when anomalies are detected.
Sedai has helped us save millions of dollars by optimizing and managing our own back-end services. But most importantly, what Sedai has done very well is allow us to respond in real time when anomalies are detected.
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Includes 30-Day Trial + Production-Ready POC
Sedai uses autonomous AI agents and reinforcement learning to balance cost, performance, and availability continuously — learning and improving over time.
Every action is vetted by rigorous safety checks and simulations; patented guardrails let you approve or veto any optimization.
Yes. Sedai supports Kubernetes (EKS/AKS/GKE & on‑prem), VMs, serverless (Lambda), storage (S3, EBS), databases and more.
Customers typically see 30–50%+ cost savings and 30%+ performance gains within months, with zero incidents.
30-day free trial + production-ready POC; then paid SaaS or self-hosted tiers optimized for your scale.
Sedai integrates with these IaC platforms to ensure that resource configurations remain in sync with the IaC files. You can integrate your preferred Git-hosting platforms with Sedai to connect your IaC in Sedai’s settings pages. Sedai offers a feature where it can map resources to IaC configuration files, providing flexibility in how infrastructure management needs are met. Sedai can also provide an option to issue an IaC pull request when operating in Recommend Mode, which will allow Sedai to provide recommendations for configuration changes but offload the execution of these changes to the IaC and its associated CI/CD pipeline.
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