Do the tests heal themselves?

Not silently. When tests fail, AI proposes grounded fixes, cause by cause, that you review and apply, and it never "fixes" a test to hide a real API bug. A project can opt in to automatic suggestions after repeated failures; they are still applied by a person unless you turn on auto-apply. Spec changes are flagged at import and create new endpoint versions you approve.

How is this different from just re-running functional tests?

Regression testing specifically focuses on detecting unintended changes in previously-working behavior. Failure analysis separates real regressions from environment, data and test problems, so the failures that remain are worth investigating.

Can I run regression tests on every commit?

Yes. The test suite runs in your CI/CD pipeline on every push, PR, or scheduled interval. Run time depends on how many tests a pack holds and how fast your API responds.

What happens when a real regression is detected?

The pipeline fails (if quality gates are configured). The platform shows which endpoints regressed, what changed, and the expected vs. actual response — giving you everything needed to diagnose and fix the issue.

Do I need to update tests when the API changes?

Change detection shows every changed endpoint and field when you import a new spec, and flags breaking changes. Tests are not edited automatically; when one fails after a change, Fix with AI proposes the update for you to review.

Can I see regression trends over time?

Yes. The analytics dashboard shows regression failure rates, most-affected endpoints, and test stability trends across builds and releases.

Regression Testing

Stop Shipping API Regressions to Production

Run your full API test suite on every deployment. Failures are grouped by cause and AI proposes fixes you review, so you fix real regressions, not noise.

Automate Regression Tests — Free See How It Works

How API regressions slip through

No regression suite

You don't have a comprehensive regression test suite for your APIs. Testing is ad-hoc or focused only on new features.

Tests are too fragile

Existing regression tests break on every minor API change. Teams spend more time fixing tests than catching bugs.

False positives everywhere

Non-breaking changes (new optional fields, updated descriptions) trigger test failures. Real regressions get lost in the noise.

Regressions found late

API regressions are caught in integration testing, staging, or production — not at the API level where they originate.

No trend visibility

You can't see if regression failures are increasing or decreasing across releases. History is lost.

Manual regression cycles

Before every release, QA runs manual regression checks. It takes days and still misses edge cases.

Why traditional regression testing breaks for APIs

API regression testing needs to be automated, comprehensive, and resilient to non-breaking changes.

Manual regression: Doesn't scale. Takes days before each release. Inconsistent coverage. Impossible to run on every commit.

Brittle scripts: Hand-written regression scripts break on cosmetic API changes. Maintaining them costs more than the bugs they catch.

UI-level regression: End-to-end UI tests are slow, flaky, and test too many layers at once. API-level regression is faster and more precise.

No regression testing: Some teams rely on production monitoring to detect regressions after they ship. By then, users are affected.

How AI-assisted regression testing works

Generate a comprehensive regression suite

AI creates tests for every endpoint from your OpenAPI spec: happy paths, error cases, edge cases, and security checks.

Run on every deployment

Execute the full regression suite in your CI/CD pipeline. Every push, every PR, every deployment is covered.

Failures explained, fixes proposed

A failed run is grouped into causes with verdicts. AI proposes grounded fixes for test defects, and a suspected product bug is never "fixed" away.

Track regression trends

See regression failure rates over time, most-affected endpoints, and test stability across releases.

Every push

Full regression on every deployment

Cause by cause

Failure analysis on every plan

Flip rate

Flaky tests flagged in regression analysis

Trends

Regression history over time

Enterprise readiness

Regression testing at enterprise scale only works when the suite stays maintainable and the evidence holds up to audit. This is where governance meets execution.

Role-based access

Five built-in roles with project-scoped assignment. Regression suite changes captured in the audit log with who, what, and when.

Audit-ready evidence

Regression runs are kept in the platform history, CI runs write JUnit XML and a JSON summary, and the audit log records changes to the suite.

On-prem self-hosting

AI test repair can run against your self-hosted LLM (Trial and Enterprise), so suite maintenance happens inside your perimeter, with no call to a cloud AI provider. Licence validation and updates contact Total Shift Left; ask us about offline licensing for air-gapped installs.

Per-branch test selection

Pick what runs per branch by choosing a pack; a pack's tag rule is re-evaluated at every run.

Quality gate enforcement

Builds fail when the pass rate falls below your threshold or a test errors. Flaky tests are flagged by flip rate in regression analysis.

Regulated industries fit

Self-hosting, per-project roles and the audit log support the controls regulated teams review. This is not a certification. See the regulated-industries pages for sector specifics.

For deployment topology see the deployment page; for the data-flow and access-control posture see platform security.

Frequently asked questions

Do the tests heal themselves?
Not silently. When tests fail, AI proposes grounded fixes, cause by cause, that you review and apply, and it never "fixes" a test to hide a real API bug. A project can opt in to automatic suggestions after repeated failures; they are still applied by a person unless you turn on auto-apply. Spec changes are flagged at import and create new endpoint versions you approve.
How is this different from just re-running functional tests?
Regression testing specifically focuses on detecting unintended changes in previously-working behavior. Failure analysis separates real regressions from environment, data and test problems, so the failures that remain are worth investigating.
Can I run regression tests on every commit?
Yes. The test suite runs in your CI/CD pipeline on every push, PR, or scheduled interval. Run time depends on how many tests a pack holds and how fast your API responds.
What happens when a real regression is detected?
The pipeline fails (if quality gates are configured). The platform shows which endpoints regressed, what changed, and the expected vs. actual response — giving you everything needed to diagnose and fix the issue.
Do I need to update tests when the API changes?
Change detection shows every changed endpoint and field when you import a new spec, and flags breaking changes. Tests are not edited automatically; when one fails after a change, Fix with AI proposes the update for you to review.
Can I see regression trends over time?
Yes. The analytics dashboard shows regression failure rates, most-affected endpoints, and test stability trends across builds and releases.

API Testing in CI/CD →API Test Coverage →API Contract Testing →OpenAPI Test Automation →Postman Alternative →

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