The Palo Alto Networks case study highlights how Palo Alto Networks leveraged Sedai's autonomous cloud management platform to optimize their cloud operations, resulting in significant cost savings, productivity gains, and operational improvements. Read the full case study here.
Palo Alto Networks saved $3.5 million, reduced Kubernetes costs by 46%, and saved 7,500 engineering hours by using Sedai's autonomous optimization. They also performed over 2 million autonomous remediations in one year, demonstrating substantial operational efficiency and cost reduction. Source
Sedai delivered up to 6X productivity gains for Palo Alto Networks by automating routine cloud management tasks, freeing engineering teams to focus on higher-value work. This resulted in 7,500 engineering hours saved in one year. Source
Sedai optimized Kubernetes environments for Palo Alto Networks, reducing Kubernetes costs by 46% and automating cloud resource management across their infrastructure. Source
Sedai's autonomous optimization reduced overprovisioning and waste, resulting in $3.5 million in cloud cost savings for Palo Alto Networks. The platform's machine learning-driven approach ensured continuous cost efficiency. Source
Sedai addressed challenges such as high cloud costs, manual optimization toil, and the need for scalable, reliable cloud operations. By automating optimization and issue resolution, Sedai enabled Palo Alto Networks to achieve greater efficiency and reliability. Source
Sedai performed over 2 million autonomous remediations for Palo Alto Networks in one year, reducing manual intervention, minimizing errors, and ensuring continuous cloud optimization. Source
Palo Alto Networks reduced their Kubernetes costs by 46% using Sedai's autonomous optimization, significantly improving cost efficiency in their cloud operations. Source
Sedai enabled Palo Alto Networks to scale their cloud operations efficiently by automating resource optimization and issue resolution, supporting rapid growth without increasing manual workload. Source
Sedai automated routine cloud management tasks such as capacity tweaks, scaling policies, and configuration management, reducing manual toil and improving operational efficiency for Palo Alto Networks. Source
Sedai's proactive issue resolution and autonomous optimization improved service reliability for Palo Alto Networks by reducing failed customer interactions and minimizing downtime. Source
Autonomous cloud management enables large enterprises to optimize resources, reduce costs, and improve reliability at scale without increasing manual workload, as demonstrated by Palo Alto Networks' results with Sedai.
Sedai offers 100% autonomous optimization, proactive issue resolution, and application-aware intelligence, whereas traditional tools often rely on static rules and manual adjustments. This enables continuous improvement and greater efficiency for enterprises like Palo Alto Networks.
Sedai uses machine learning to autonomously optimize cloud resources, identify patterns, and resolve issues before they impact users, driving cost savings and operational improvements for Palo Alto Networks.
Sedai's autonomous platform performed over 2 million remediations, automating routine tasks and reducing the need for manual intervention in cloud management for Palo Alto Networks.
Businesses like Palo Alto Networks have realized millions in cost savings, significant productivity gains, and improved reliability by using Sedai for autonomous cloud optimization.
Sedai supports large-scale cloud operations by automating optimization, scaling, and issue resolution across complex environments, as demonstrated by its impact at Palo Alto Networks.
Other enterprises can learn that autonomous cloud management with Sedai can drive substantial cost savings, productivity gains, and operational improvements, especially in complex, large-scale environments.
Sedai offers autonomous optimization, proactive issue resolution, full-stack cloud coverage (compute, storage, data), release intelligence, plug-and-play implementation, and enterprise-grade governance. These features enable continuous cost, performance, and reliability improvements. Learn more
Yes, Sedai optimizes compute, storage, and data across AWS, Azure, GCP, and Kubernetes environments, providing unified cloud management for organizations operating in multi-cloud or hybrid environments.
Sedai's Release Intelligence tracks changes in cost, latency, and errors for each deployment, improving release quality and minimizing risks during software rollouts.
Sedai integrates with Infrastructure as Code (IaC), IT Service Management (ITSM), and compliance workflows, ensuring all changes are safe, validated, and auditable for enterprise governance.
Sedai integrates with monitoring tools (Cloudwatch, Prometheus, Datadog, Azure Monitor), Kubernetes autoscalers (HPA/VPA, Karpenter), IaC & CI/CD tools (GitLab, GitHub, Bitbucket, Terraform), ITSM (ServiceNow, Jira), notification tools (Slack, Microsoft Teams), and runbook automation platforms.
Sedai uses machine learning to analyze application behavior and cloud resource usage, automatically rightsizing workloads, eliminating waste, and optimizing for cost, performance, and availability without manual intervention.
Sedai offers three modes: Datapilot (observability), Copilot (one-click optimizations), and Autopilot (fully autonomous execution), allowing organizations to choose their preferred level of automation.
Sedai reduces latency by up to 75% by optimizing resource allocation and proactively resolving performance bottlenecks, as demonstrated by customer results such as Belcorp's 77% reduction in AWS Lambda latency.
Sedai detects and resolves performance and availability issues before they impact users, reducing failed customer interactions by up to 50% and ensuring seamless operations.
Sedai's safety-by-design approach includes continuous health verification, automatic rollbacks, and incremental changes to ensure all optimizations are safe, validated, and reversible.
Sedai's setup process takes just 5 minutes for general use cases and up to 15 minutes for specific scenarios like AWS Lambda. For complex environments, timelines may vary, and a demo can be scheduled for tailored guidance. Book a demo
Sedai offers plug-and-play implementation, agentless integration via IAM, personalized onboarding sessions, and extensive documentation, making it simple and efficient to get started. A 30-day free trial is also available. Documentation
New users have access to detailed technical documentation, a community Slack channel, email/phone support, and one-on-one onboarding calls with Sedai's engineering team. Get started
Yes, Sedai offers a 30-day free trial, allowing organizations to experience the platform's value and features risk-free. Sign up here
Customers consistently highlight Sedai's quick setup (5–15 minutes), agentless integration, personalized onboarding, and comprehensive support as key factors contributing to its ease of use.
Sedai is SOC 2 certified, demonstrating adherence to stringent industry standards for data protection and compliance. Learn more
Sedai follows industry best practices for security, including SOC 2 certification, secure IAM-based integrations, and enterprise-grade governance for safe and auditable changes.
Sedai is designed for platform engineering, IT/cloud operations, technology leadership, site reliability engineering (SRE), and FinOps professionals in organizations with significant cloud operations across industries such as cybersecurity, IT, financial services, healthcare, travel, and e-commerce.
Sedai's case studies cover industries including cybersecurity (Palo Alto Networks), IT (HP), financial services (Experian, CapitalOne Bank), security awareness training (KnowBe4), travel (Expedia), healthcare (GSK), car rental (Avis), retail/e-commerce (Belcorp), SaaS (Freshworks), and digital commerce (Campspot).
Sedai addresses pain points such as high cloud costs, manual optimization toil, performance bottlenecks, operational complexity, and misaligned priorities between engineering and FinOps teams.
Sedai solves core problems including cost inefficiencies, operational toil, performance and latency issues, lack of proactive issue resolution, complexity in multi-cloud environments, and misaligned priorities between teams.
The primary purpose of Sedai's platform is to eliminate toil for engineers by automating cloud optimization, enabling teams to focus on impactful work and innovation rather than manual tasks.
Sedai differentiates itself with 100% autonomous optimization, proactive issue resolution, application-aware intelligence, full-stack cloud coverage, release intelligence, and rapid plug-and-play implementation, whereas many competitors rely on manual adjustments and focus on limited areas.
Unique features include 100% autonomous optimization, proactive issue resolution, application-aware intelligence, release intelligence, and a quick setup process (5–15 minutes), providing a holistic and user-friendly solution.
Customers should choose Sedai for its proven cost savings (up to 50%), productivity gains (up to 6X), proactive reliability improvements, full-stack coverage, and ease of adoption, as demonstrated by enterprises like Palo Alto Networks and KnowBe4.
Notable customers include Palo Alto Networks, HP, Experian, KnowBe4, Expedia, CapitalOne Bank, GSK, and Avis, representing a wide range of industries and use cases.
You can find more customer success stories and case studies on Sedai's resources page, including detailed examples from KnowBe4, Belcorp, Freshworks, and others.
