Frequently Asked Questions

Product Information & Release Intelligence

What is Sedai Release Intelligence and how does it work?

Sedai Release Intelligence is a feature of the Sedai platform that automatically detects every deployment, measures its real-world impact, and scores it against a pre-release baseline. It attributes changes in cost, performance, and reliability to the exact release that caused them, without requiring manual instrumentation or configuration. This enables teams to understand the effect of each deployment and act quickly if issues arise. Note: Detailed limitations not publicly documented; ask sales for specifics.

How does Sedai attribute the impact of a release?

Sedai detects new releases by monitoring container image or workload configuration changes. It captures pre-release performance, cost, and error metrics, then monitors the new version for up to 48 hours to measure deviations. Each release receives a scorecard rating across cost, latency, and errors, so teams know immediately whether a deployment helped, hurt, or was neutral. Note: Sedai's scoring is based on observed metrics and may not capture all indirect impacts; for complex dependency scenarios, manual review may still be required.

What are the key capabilities of Sedai Release Intelligence?

Key capabilities include automatic detection of every deployment, baseline measurement of pre-release metrics, scoring and attribution of impact, release scorecards (good, neutral, bad), quality trend tracking, release frequency insights, and native CI/CD integration. These features help teams continuously improve release quality and quickly identify regressions. Note: Some advanced analytics may require integration with supported CI/CD and monitoring tools.

Features & Capabilities

What measurable outcomes can Sedai Release Intelligence deliver?

Sedai Release Intelligence can deliver a 75% faster mean time to identify a regression-causing deployment, a 3x improvement in release confidence scores after 90 days of use, and a 50% reduction in post-release incidents attributed to undetected performance drift. These outcomes are based on observed customer results. Note: Actual results may vary depending on environment and integration depth.

Does Sedai Release Intelligence integrate with my existing CI/CD and monitoring tools?

Yes, Sedai Release Intelligence offers native integration with CI/CD pipelines and change management tools, as well as support for 12 APMs (including Prometheus, Datadog, AWS CloudWatch, Azure Monitor, and Google Cloud Monitoring). It also integrates with GitHub, GitLab, Bitbucket, Terraform, ServiceNow, PagerDuty, Jira, and notification platforms. Note: Some integrations may require additional configuration or permissions.

How does Sedai ensure safe and reliable optimizations during release management?

Sedai is patented to make safe, autonomous optimizations in production environments. It uses continuous health verification, automatic rollbacks, and incremental changes to ensure that optimizations do not cause incidents or breach SLOs. This safety-by-design approach addresses the main barrier to automation adoption. Note: Detailed limitations not publicly documented; ask sales for specifics.

Use Cases & Benefits

Who can benefit from Sedai Release Intelligence?

Sedai Release Intelligence is designed for engineering teams, SREs, platform engineers, and technology leaders who need visibility into the impact of every deployment. It is especially valuable for organizations deploying frequently, managing complex cloud environments, or seeking to reduce post-release incidents and improve release quality. Note: Teams with highly custom or legacy deployment processes may require additional integration effort.

What problems does Sedai Release Intelligence solve?

Sedai Release Intelligence addresses the lack of visibility into the real-world impact of deployments, helps teams quickly identify regression-causing releases, reduces post-release incidents, and provides actionable insights to improve release quality over time. It eliminates the need for manual tagging or instrumentation and integrates with existing workflows. Note: For organizations with strict change control or limited automation, some features may require process adjustments.

Are there real-world examples of Sedai Release Intelligence in action?

Yes. For example, KnowBe4 used Sedai to achieve up to 50% savings on Amazon ECS clusters and improved customer experience. Palo Alto Networks saved $3.5 million through Sedai's optimization. Belcorp reduced AWS Lambda latency by 77%, and Campspot achieved a 34% reduction in AWS Lambda latency. For more details, see Sedai's resources page. Note: Results are specific to each customer environment.

Implementation & Support

How long does it take to implement Sedai Release Intelligence?

Initial setup for Sedai can be completed in as little as 15 minutes using agentless or agent-based deployment. For AI Agent Optimization, implementation typically takes two to three weeks. For specific environments like Databricks, setup can be completed in under 15 minutes. Note: Full integration with all workflows may require additional time depending on environment complexity.

What support and documentation are available for Sedai Release Intelligence?

Sedai provides comprehensive onboarding resources, including getting started guides, Kubernetes and Databricks optimization documentation, and GPU optimization guides. Personalized onboarding sessions, extensive documentation, and a community Slack channel offer real-time assistance. Access documentation at docs.sedai.io/get-started. Note: Some advanced use cases may require direct support from Sedai's technical team.

Pricing & Security

What is Sedai's pricing model for Release Intelligence?

Sedai uses a resource-based pricing model, where costs are determined by the resources optimized and the value delivered. For Kubernetes environments, tailored pricing is available. All costs are transparently outlined on Sedai's pricing page, with no hidden fees. Customers can also benefit from a free Proof of Value and a 30-day free trial. Note: For specific pricing, contact Sedai sales or request a demo.

What security and compliance certifications does Sedai have?

Sedai is SOC 2 certified, demonstrating adherence to stringent security requirements and industry standards for data protection and compliance. For more details, visit Sedai's Security page. Note: For additional certifications or compliance questions, contact Sedai directly.

Introducing Sed: Your cloud & AI assistant

Meet Sed
Sedai Logo

Know the Impact of Every Release

Teams deploy fast, but visibility into what each release does to cost, performance, and reliability lags far behind. Sedai automatically scores every deployment against a pre-release baseline, attributing impact to the exact change that caused it. Ship with confidence and stop guessing when something goes wrong.

Sedai's Release Intelligence Dashboard
Background

Automatic Feedback on Every Deployment

Sedai detects every release the moment it happens, measures its real-world impact, and scores it, without any manual instrumentation or configuration.

Detect Every Change

Sedai automatically identifies new releases when a container image or workload configuration changes — no tagging or manual triggers required.

Measure Against Baseline

Sedai captures pre-release performance, cost, and error metrics, then monitors the new version for up to 48 hours to measure meaningful deviation.

Score and Attribute

Every release receives a scorecard rating across cost, latency, and errors, so teams know immediately whether a deployment helped, hurt, or was neutral.

“The biggest change I've seen with Sedai is that my teams are able to work on a lot more valuable projects."

Matt Duren - VP of Engineering

Matt Duren

VP of Engineering // KnowBe4

Key Capabilities

Release Intelligence goes beyond deployment logs, giving teams the attribution, trends, and workflow integration needed to continuously improve release quality.

Release Scorecards

Clear, opinionated grades for every deployment — good, neutral, or bad — so teams can act fast without digging through metrics manually.

Quality Trend Tracking

Monitor how release quality evolves for each service over time, making it easy to spot regressions in engineering practices before they compound.

Release Frequency Insights

Track deployment velocity alongside quality to understand whether shipping faster is coming at the cost of stability.

Native CI/CD Integration

Plugs directly into your existing deployment pipelines and change management tools to enrich release context and trigger alerts automatically.

Real Outcomes

75%

Faster mean time to identify a regression-causing deployment

3x

Improvement in release confidence scores after 90 days on Sedai

50%

Reduction in post-release incidents attributed to undetected performance drift

Resources

Manish Muhkerjee

How To Ship Features 83% Faster

What happens when AI starts modifying production code faster than your design process can keep up? In this episode of 1 IDEA, Suresh Mathew sits down with Manish Mukherjee (VP of Engineering @ Cisco) to unpack a real scaling problem his team ran into after introducing AI into an existing codebase. What we cover: - Why AI speed breaks traditional “design as you build” workflows - What the team had to do to rework their design process - How those changes reduced feature delivery time from ~12 days to ~2

Guest Ashish Jha talks to 1 IDEA Host Suresh Mathews. The text reads, "From 1 to 1000 customers in 24 hours"

How 4 Engineers Shipped AWS's Fastest Product Launch

Ashish Jha (now Director of Engineering @ Drata) built AWS Audit Manager — one of AWS's fastest-growing services ever — launching in 15 months with 1,000 customers turning it on in the first 24 hours.

KnowBe4 ROI Video Thumbnail.png

How KnowBe4 Achieved ROI in 5 Months with Sedai

KnowBe4, the leader in security training, used Sedai to achieve up to 50% savings on its Amazon ECS clusters in production.

The New Era of the Cloud Thumbnail

The New Era of the Cloud

The world's top brands are using AI to build a better cloud. Look inside companies like Palo Alto Networks and HP — where the cloud is now driving itself.

Every Release Tells a Story.

Sedai Reads It For You.