Frequently Asked Questions

Product Information

What is Sedai and what does it do?

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. Sedai's platform delivers up to 53% cost savings, 30% latency reduction, and 33% reduction in SRE workload by continuously adapting to changes in microservices and learning from previous optimizations. Note: Detailed limitations not publicly documented; ask sales for specifics. Source

What are the main features and capabilities of Sedai?

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, incremental changes), release intelligence, and plug-and-play implementation. It supports Datapilot (observability), Copilot (one-click optimizations), and Autopilot (fully autonomous execution) modes. Note: Best fit for teams seeking autonomous, application-aware optimization; teams requiring deep manual control may want to consider alternatives. Source

What types of deployment options does Sedai offer?

Sedai provides both agentless SaaS and agent-based SaaS solutions. The agentless option connects securely to your cloud using IAM roles (Amazon EKS) or Azure AD roles (Azure AKS). The agent-based option uses Kubernetes RBAC for secure connectivity within your environment. Note: On-premise deployment details are not publicly documented; contact Sedai for more information. Source

Pricing & Plans

What is Sedai's pricing model?

Sedai uses a volume-based pricing model, charging based on the specific resources optimized (e.g., Kubernetes pods, ECS tasks, VMs). Pricing is transparent, adapts to your usage, and includes a free tier and a 30-day free trial. For Kubernetes environments, Sedai recommends booking a demo to determine the best pricing structure. Note: Exact pricing figures are not publicly listed; contact Sedai for a custom quote. Source

Features & Capabilities

What integrations does Sedai support?

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: Integration with other platforms may require custom setup; check documentation for details. Source

What technical documentation is available for Sedai?

Sedai provides a Getting Started Guide, a Kubernetes Optimization Guide, and a 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. Source

Use Cases & Benefits

Who can benefit from using Sedai?

Sedai is designed for IT/Cloud Operations, FinOps, Technology Leadership, Platform Engineering, and Site Reliability Engineering (SRE) roles. It is used by organizations in cybersecurity, financial services, healthcare, e-commerce, IT, consumer goods, and digital commerce. Note: Teams with highly specialized, non-cloud-native environments may require additional integration work. Source

What business impact can customers expect from Sedai?

Customers typically achieve up to 50% cloud cost reduction, 75% latency reduction, 50% fewer failed customer interactions, and up to 6X productivity improvements. Financial payback is typically under six months, with ROI greater than 400%. For example, KnowBe4 saved $1.2 million and Palo Alto Networks saved $3.5 million using Sedai. Note: Results may vary based on environment complexity and adoption scope. Source

What problems does Sedai solve for engineering and operations teams?

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. Note: Some highly regulated or legacy environments may require additional validation before adopting autonomous optimization. Source

Implementation & Support

How long does it take to implement Sedai and how easy is it to start?

Initial onboarding takes about 15 minutes for agentless or agent-based deployment to begin reading metrics. Additional setup for CI/CD and integrations may require more time depending on environment complexity. Sedai offers a plug-and-play process and integrates with existing tools. Note: Complex environments may require additional configuration and support. Source

Security & Compliance

What security and compliance certifications does Sedai have?

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 are not publicly listed; contact Sedai for specifics. Source

Customer Success & Case Studies

Can you share specific case studies or success stories of Sedai customers?

Yes. KnowBe4 achieved up to 50% cost savings and saved $1.2 million on AWS. Palo Alto Networks saved $3.5 million. Belcorp reduced AWS Lambda latency by 77%. Campspot achieved a 34% reduction in Lambda latency. Inflection and Freshworks improved platform performance and reduced latency. See more at sedai.io/customers. Note: Results are customer-specific and may not be representative for all users. Source

What industries are represented in Sedai's case studies?

Sedai's case studies include customers from 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 industries may have published case studies; contact Sedai for more examples. Source

Sedai now optimizes AI agents!

Read the news
Sedai Logo

All Posts

6 Best Practices for Optimizing GKE Costs

6 GKE Cost Optimization Best Practices for 2026

Cut GKE costs in 2026 with 6 best practices: rightsizing, autoscaling (HPA/VPA/CA/KEDA), CUDs, Spot VMs, and Autopilot vs Standard mode.

FinOps & Engineering Both Want to Lower BigQuery Costs. So Why Hasn't Anyone?

FinOps & Engineering Both Want to Lower BigQuery Costs. So Why Hasn't Anyone?

If your team is using BigQuery at scale, there's a good chance your FinOps and engineering teams are both trying to lower the bill, but neither are succeeding. This is why.

Sedai BigQuery Optimization

What If Your BigQuery Slots Managed Themselves?

Sedai BigQuery optimization analyzes, right-sizes, and optimizes your reservations and autoscale settings automatically.

Google Cloud, Optimized

Autonomous Optimization for GCE and Google Cloud Storage

cloud workload automation

Cloud Workload Automation Guide With 9 Top Software for 2026

Optimize cloud workloads in 2026 with our expert guide. Discover 9 top automation tools to increase performance, reduce costs, and simplify operations.

Challenges with cloud optimization

22 Top Challenges with Cloud Cost Optimization & Solutions

Address key challenges with cloud optimization: reduce costs by tackling cloud waste, performance issues, and pricing complexity. Enhance your strategy now!

Optimizing Google Dataflow for High Availability and Performance

Optimizing Google Dataflow for High Availability and Performance

Tune and optimizing Google Dataflow for maximum availability and performance.

How to Estimate Google Dataflow Costs and Pricing

How to Estimate Google Dataflow Costs and Pricing

Understand Google Dataflow costs, pricing components, and cost-saving strategies. Learn how Sedai automates Dataflow optimization safely.

Google Cloud SQL: The Practical Guide For 2025

Google Cloud SQL: The Practical Guide For 2025

Learn how to optimize Google Cloud SQL for performance and cost. Explore best tools and strategies plus Sedai’s AI-driven savings.