AI regression testing that follows every code change
Focus each release on the tests most likely to fail. The Regression Testing Agent uses change context, runs resilient browser checks, and returns evidence your team can act on.
See how targeted regression testing fits your release workflow.
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Capabilities
Automated regression testing focused on release risk
Run the coverage that matters for each change without losing the baseline checks your team requires.
Change-impact test selection
Map code changes, affected services, release risk, and historical failures to the regression tests that matter most. Keep required baseline coverage while prioritizing high-risk paths.
Resilient browser execution
Adapt to low-risk selector drift during automated regression testing and record every adjustment for review. Minor interface changes no longer have to obscure real product failures.
Flake versus regression classification
Compare retries, run history, failure patterns, and release context to separate likely flaky tests from reproducible software regressions.
Workflow
How the Regression Testing Agent works
Move from release context to a reviewable regression decision in three controlled steps.
1. Connect release context
Provide the change set, affected services, existing test cases, target environment, and release policies.
2. Run a risk-focused suite
The agent selects and executes the most relevant regression checks while preserving every required baseline test.
3. Review and gate
Inspect failures, likely flakes, screenshots, logs, and change context before approving or blocking the release.
Evidence
Regression evidence developers can reproduce
Every result explains what ran, why it ran, and what changed when a test failed.
Change-to-test coverage map
See which changed components influenced test selection, which critical paths were covered, and which areas still need human review.
Complete run evidence
Review pass, fail, and skip results with screenshots, video, browser logs, timing, and the expected versus observed behavior.
Failure and flake history
Compare the current result with previous runs, retries, and related failures before treating a signal as a release regression.
Platform
A controllable platform for AI regression testing
Deploy, trigger, govern, and audit the agent according to your engineering and security requirements.
Self-hosted with an open-source model
Use the managed service or deploy inside your VPC or on-premises with an approved open-source model. Keep code, credentials, test data, and results within your environment.
Webhook or scheduler triggers
Run after a deployment, pull request, release webhook, CI/CD event, API call, or recurring schedule. Manual runs remain available.
Safe access to private environments
Test staging sites, internal applications, and protected services with scoped credentials, allowlists, and read-only defaults.
Custom rules and thresholds
Set mandatory regression checks, severity thresholds, exclusions, retries, and team-specific release policies.
Change-aware execution
Use code diffs, changed services, requirements, and risk labels to prioritize the checks most relevant to a release.
Evidence with every finding
Capture pass, fail, and skip results with applicable screenshots, video, logs, traces, diffs, and source context.
Human-controlled release gates
Choose whether a finding informs the team, opens a defect, waits for approval, or blocks a release.
Connected delivery workflow
Route regression results and evidence into TestCollab, issue trackers, source control, team channels, and CI/CD pipelines.
Audit-ready history and portable results
Retain configurations, model versions, runs, overrides, and approvals. Export portable results in formats such as JSON, JUnit, SARIF, and PDF where applicable.
FAQ
Answers teams look for
What is an AI regression testing agent?
An AI regression testing agent selects and runs tests that verify existing behavior after a software change. It uses release context to focus automated regression testing on the areas with the greatest risk.
How does the agent decide which regression tests to run?
It evaluates code changes, affected components, dependencies, historical failures, risk labels, and required baseline tests. Your team remains in control of mandatory coverage and release thresholds.
Can it use our existing automated regression tests?
Yes. The agent can prioritize existing test cases and supported automated suites, then identify high-risk gaps that need additional coverage. Teams do not need to replace their full regression suite.
How does it handle flaky tests?
The agent compares retry behavior, failure history, and evidence from the current run. It reports likely flakes separately from reproducible regressions so teams can apply the appropriate release policy.
Put regression testing on every release
See how a change-aware agent can focus coverage, capture evidence, and keep your team in control.
