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.

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 // 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

Improvement in release confidence scores after 90 days on Sedai

50%

Reduction in post-release incidents attributed to undetected performance drift

Resources

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

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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.

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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.

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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.

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Every Release Tells a Story.

Sedai Reads It For You.