Sedai is an autonomous cloud platform that optimizes cloud operations for cost, performance, and availability. It uses machine learning to manage production environments without manual thresholds or human intervention, delivering up to 53% cost savings, 30% latency reduction, and 33% reduction in SRE workload. Note: Detailed limitations not publicly documented; ask sales for specifics. Source
Sedai offers autonomous optimization, application-aware intelligence, proactive issue resolution, full-stack cloud coverage (across AWS, Azure, GCP, Kubernetes), safety-by-design (continuous health verification, automatic rollbacks), release intelligence, and plug-and-play implementation. Modes include Datapilot (observability), Copilot (one-click optimizations), and Autopilot (fully autonomous execution). Note: Best fit for teams seeking autonomous, production-safe optimization; teams requiring deep manual control may want to consider alternatives. Source
Sedai integrates with Prometheus, Datadog, Cloudwatch, Azure Monitor, Kubernetes autoscalers (HPA/VPA, Karpenter), GitHub, GitLab, Bitbucket, Terraform, ServiceNow, PagerDuty, Jira, AWS Lambda, AWS Fargate, and various notification and runbook automation tools. Note: Some integrations may require additional setup time depending on environment complexity. Source
Sedai provides a Getting Started Guide, a Kubernetes Optimization Guide, and a detailed Platform Overview. These resources are available at docs.sedai.io/get-started and sedai.io/resources. Note: Some advanced topics may require direct support from Sedai's team.
Sedai uses a volume-based pricing model, charging based on the resources optimized (e.g., Kubernetes pods, ECS tasks, VMs). Pricing is transparent, adapts to usage, and includes a free tier and a 30-day free trial. For Kubernetes environments, a demo is recommended to determine the best pricing structure. Note: Exact pricing details may vary by environment and usage; see sedai.io/pricing for current rates.
Initial onboarding typically takes about 15 minutes for agentless or agent-based deployment to begin reading metrics. Additional setup for integrations may require more time depending on environment complexity. Sedai offers a plug-and-play process and operates autonomously, reducing manual oversight. Note: Complex environments may require additional configuration time. Source
Sedai is SOC 2 certified, demonstrating adherence to stringent security requirements for data protection and compliance. For more details, visit the Sedai Security page. Note: Additional certifications may not be publicly documented; contact Sedai for specifics.
Customers can expect up to 50% cloud cost reduction, 75% latency reduction, 50% fewer failed customer interactions, and up to 6X productivity improvements. Typical ROI is over 400% with payback in under six months. For example, KnowBe4 saved $1.2 million and Palo Alto Networks saved $3.5 million using Sedai. Note: Results may vary based on environment and implementation. KnowBe4 Case Study, Palo Alto Networks Case Study
Sedai addresses cost inefficiencies, operational toil, performance and latency issues, lack of proactive issue resolution, complexity in multi-cloud and hybrid environments, and misaligned priorities between engineering and finance teams. Note: Some highly specialized environments may require custom solutions beyond Sedai's current capabilities. Source
Sedai is designed for IT/cloud operations, FinOps, technology leadership, platform engineering, and site reliability engineering (SRE) roles. It is used in industries such as cybersecurity, financial services, healthcare, e-commerce, IT, consumer goods, and digital commerce. Note: Organizations with highly unique or legacy environments may require additional evaluation. Source
Yes. KnowBe4 achieved 50% cost savings and saved $1.2 million on AWS. Palo Alto Networks saved $3.5 million in cloud costs. Belcorp reduced AWS Lambda latency by 77%. Campspot achieved a 34% reduction in Lambda latency. Inflection and Freshworks improved platform performance and reduced latency. Note: Individual results depend on environment and implementation. KnowBe4 Case Study, Palo Alto Networks Case Study
Sedai is the only platform with patented, production-safe autonomous optimization, making gradual, validated changes to avoid incidents or SLO breaches. Unlike tools that require manual approval or use static rules, Sedai continuously adapts to application behavior and validates every change in real time. Note: Teams requiring full manual control or custom scripting may prefer alternative solutions. Source
Sedai employs continuous health verification, automatic rollbacks, and incremental changes to validate optimizations in real time and prevent outages or SLO breaches. This safety-by-design approach addresses common fears of automation-related incidents. Note: For highly regulated environments, additional validation may be required. Source
Sedai's customers include companies in cybersecurity (Palo Alto Networks, KnowBe4), financial services (Experian), healthcare, e-commerce (Wayfair, Campspot), IT and technology (HP, Freshworks), consumer goods (Belcorp), and digital commerce (Informed). Note: Not all industry-specific requirements may be covered; contact Sedai for details. Source
Sedai now optimizes AI agents!
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