AI-Powered Quality Engineering. From Requirement to Release Confidence.
The agentic QA workspace that turns connected requirements into testable quality intelligence — manual and automated coverage, execution evidence, defects, and release insight. Six specialist AI agents, one connected quality record.
Connect
Jira, Confluence and more
Collaborate
specialist AI agents
Prove
quality with evidence
One connected quality flow
Every requirement becomes a quality decision — not a document waiting for manual interpretation.
One AI-assisted path from a pasted requirement to saved analysis, editable test coverage, Playwright automation, execution evidence, and release risk — with an AI judge scoring every stage.
Paste your requirement
- Copy-paste requirement text
- SauceDemo-style feature specs
- Any product scenario
Analyze with AI
- Business rules
- Acceptance criteria
- Risks and edge cases
Design coverage
- Editable manual cases
- Positive and negative paths
- Traceable test data
Execute with evidence
- Playwright automation
- Local Docker / remote runner
- Pass/fail results
Act on risk
- Release confidence
- Precision & accuracy per stage
- Executive visibility
Available today
AI agents that make quality work structured, visible, and actionable.
Currently supporting copy-pasted requirements only — MCP connections (Jira, Confluence, GitHub, Zephyr, TestRail, Pinecone) are coming soon.
Requirement Intelligence Agent
Reads requirements (copy-pasted) and produces executive summaries, business rules, acceptance criteria, risks, edge cases, scenarios, and test data.
From raw requirement to requirement intelligence
Manual Test Case Agent
Generates review-ready, editable manual test cases from saved analysis and organises them by product and module.
Review-ready, editable coverage by product and module
Automation Script Agent
Transforms approved coverage into Playwright (TypeScript) UI automation scripts.
Approved coverage → framework-ready test scripts
Execution & Defect Agent
Runs controlled test cycles, records pass/fail evidence, captures screenshots, and creates rich Jira bugs from failed tests.
Controlled cycles, pass/fail evidence, rich defects
DevOps Execution Agent
Triggers, monitors, and interprets runs through Jenkins and connected CI/CD tools, linking pipeline evidence back to the relevant test cycle.
Trigger, monitor, interpret pipeline runs
Quality Intelligence Agent
Correlates manual and automated outcomes, defects, coverage, and delivery signals to explain release readiness and where action is needed.
Release readiness, explained
Integration-first
A shared quality workspace for product, QA, engineering, and leaders.
Requirement intelligence
Paste a requirement and get business rules, acceptance criteria, risks, edge cases, and test data — scored by an AI judge.
Traceability by design
Follow the thread from requirement to AI analysis, generated tests, execution result, defect, and release confidence.
Release intelligence
See precision/accuracy per stage, release confidence, active risks, and the work that still needs attention.
Free-model AI
Runs entirely on free OpenRouter models — a hard guard refuses paid models. No accidental spend.
See QAE2E in action
Turn your next requirement into release-ready QA intelligence.
Bring one story, one module, or one release process. Watch the six agents connect the dots from intent to evidence — with real, editable artifacts and a release-confidence gauge.