Launch AI-first workflows for QA testing in minutes. Automate test runs, environment setup, and result reporting so teams ship quality releases without last-minute scrambles.
Built for QA, Engineering, and Release Teams
Kick off flows from pull requests, merges, nightly schedules, or issue labels
AI steps summarize failures, pinpoint flaky tests, and suggest likely fixes
Provision test data and environments automatically before suites run
430+ connectors for repos, CI tools, test frameworks, clouds, and chat
Sensitive details never appear in logs due to data masking.
Run in our secure cloud or self-host for complete control.
Catch Regressions Early And Keep Releases Moving
Manual orchestration slows testing and obscures failures. Centralizing triggers, data seeding, and reporting cuts cycle time, exposes risk quickly, and keeps engineers focused on real defects.
SOC 2 Type II cloud or self-hosted deployment
Disconnected apps slow teams down and create errors.
Activepieces fixes that by giving you 400+ integrations in one platform.
Run unit, integration, and end-to-end suites on PR, tag, or schedule. Fan out tests in parallel, shard large suites, and gate merges on required checks.
Seed fixtures and synthetic users, spin up ephemeral environments, and inject secrets per environment. Tear down automatically to control costs.
Aggregate logs across jobs, cluster similar failures, and surface flaky tests. Generate concise failure digests for Slack and create issues with reproduction steps.
Publish dashboards with pass rates, duration trends, and coverage deltas. Route release checklists to approvers and pause deployment until criteria are met.
Frequently asked questions
What can we automate for QA?
You can automate test execution on PRs, environment provisioning, data seeding, and report delivery. Flows also open bugs automatically with logs and repro steps to reduce triage time.
How does AI help analyze failures?
AI clusters similar errors, flags flakiness, and maps stack traces to likely modules or recent commits. Engineers get an actionable summary instead of sifting through raw logs.
How do we prevent flaky tests from blocking releases?
Mark suspected flakies automatically after repeated non-deterministic failures, and then quarantine them to a separate lane and require stability before re-enabling as a gate.
How do leads track quality over time?
Dashboards show pass/fail rates, test duration, coverage changes, and defect reopen rates. Weekly summaries go to Slack or email, so trends are visible to the whole team.