Agentic QA that verifies its own work.
The AI proposes. A deterministic gate decides. From requirement to release, with confidence.
- ✓Nothing ships on AI confidence alone
- ✓Every verdict comes with a reason
- ✓One engine for every test type
- ✓A full audit trail
- ✓Contract matches the spec
- ✓Response schema valid
- ✓Status 201 returned
The gap shows up at every stage, not just in testing.
Testing, release and production each break in their own way. Nothing that is learned in one stage reaches the next, so the same gaps open on every release.
- ✕Test scripts are hand-written and brittle. They break every time the app changes.
- ✕Web, API, performance, security and regression run as separate silos.
- ✕Coverage is tracked to a checklist, not to the actual requirement.
- ✕Go / No-Go is decided on gut feel, not on test evidence.
- ✕No risk model tied to what actually failed, and why.
- ✕Late-stage churn shows up too late to react, and the schedule slips.
- ✕Production issues surprise teams that had no visibility beforehand.
- ✕Patches get re-tested blindly, from zero, every time.
- ✕Nothing that happens live flows back into test coverage.
↺ ✕ No loop back from live into testing
One closed loop, from requirement to verified test.
Scroll and follow one requirement round the loop. The AI writes and runs the test, a fixed rule decides, a person signs off anything risky, and what it learned comes back round.
Loop reads the requirement and drafts the test. The AI writes it, but it never gets to judge it.
One engine generates every kind of test you need.
Point Loop at a requirement or an existing surface, and it generates, executes and verifies the tests. No scripts written by hand, and no separate tool per test type.
Full user journeys, verified against how the app actually behaves.
journey cart → pay → confirmContracts, schemas and endpoint behaviour, from the spec or discovery.
POST /orders · contract v2Latency and load, measured only from successful responses.
p95 counted on 2xx onlyRe-run automatically whenever the requirement or the app changes.
app changed → suite re-runsNegative and adversarial cases, judged for how the API fails.
bad token → 401, not 500Every patch re-tested against the same verified baseline.
patch vs verified baselineThe AI never grades its own homework.
Every result passes through a deterministic gate a human can audit. Confidence is never the reason something ships.
Proposes the test. It never decides if it passed.
- Passedreason status 201, contract met
- Failedreason status 500, expected 201
- Contract-violatedreason orderId missing from the response
- Driftedreason field total renamed to amount in v2
- Blockedreason staging unreachable, run paused
- 11:02:11gatepassedrule: status = 201, contract v2 met
Test results become release intelligence, not just a checklist.
The same verified evidence that runs your tests also drives release and delivery decisions, across the whole lifecycle, not only at the end.
- /orders total → amountHigh
- checkout UI button textLow
- /payments new retryHigh
- profile page layoutLow
Most agentic QA tools trust the model. Loop doesn’t have to.
The difference is who makes the call. In most tools the model writes the test and grades it too. In Loop a separate gate decides, and a person approves risk.
- Pass / fail decision✕Typical agentic QA tool: The LLM’s own output✓Loop: A deterministic gate, independent of the model
- What gets tested✕Typical agentic QA tool: Throwaway scripts, regenerated each run✓Loop: A reusable knowledge asset that compounds
- Risk approvals✕Typical agentic QA tool: Client-side confirmation, easy to bypass✓Loop: Server-enforced, a named approver, reason logged
- Lifecycle coverage✕Typical agentic QA tool: Test execution only✓Loop: Development through post-go-live
- Change handling✕Typical agentic QA tool: Full re-write on drift✓Loop: Heal / repair lanes scoped to the actual change
Better software. Safer releases. Happier customers.
Higher quality, faster, safer, together. Each one comes from a part of the loop you have already seen.
- ✓ status is 201✓ contract met✕ AI grade ignoredHigher quality
A fixed gate decides every result, so nothing ships on AI confidence alone.
From The gate - requirement→ 6 test types→ re-run on changeFaster
Tests are generated, run and re-run for you. No scripts written by hand.
From One engine - repair touches payments→ approver signs off→ reason loggedSafer
Risky changes wait for a named approver, and every decision is logged.
From Heal / repair + audit - AI proposesRule decidesPerson approves riskTogether
AI does the repetitive work. People decide what matters.
From Proposer / verifier
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