Regression Guard for software releases
Catch unintended behaviour before it ships

Early compares each release candidate with production behaviour and shows the business flows put at risk.

Early Regression Guard showing a cross-component Regression and the business flow it affected

From code change to release decision

Early release candidate overview showing component analysis and release readiness
Anchor production
Start with the business flows and behaviours already working in production.
Analyze the candidate
Compare a PR or release candidate with that baseline.
Surface changed behaviour
Narrow the impact map to the behaviours that actually differ.
Track readiness
Keep regressions, expected changes and component readiness in one release record.

A different signal for release decisions

Understand the change in the system, not only in the files.

Business-flow impact
See which customer and operational flows a change reaches.
Cross-component reach
Trace impact across configured component relationships.
Production comparison
Compare the candidate with the behaviour users already rely on.
Clear classification
Classify changed behaviour as Expected or Regression.
Traceable evidence
Keep each result linked to its PR, commit, author and run.

Release risk in practice

You didn't touch it. It broke anyway.
The bottleneck in software delivery has shifted from writing code to verifying what changed.
Reviewing the Diff Was Never the Hard Part
AI review made the local problem smaller. It made the systemic one bigger.
Verifying AI-Generated Code Is a Different Job Than Reviewing It
The hard part is no longer spotting ugly code. It is proving a clean change did not alter behavior the model never understood.

Remember your last regression?

Use it to test Early.

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