Standalone Agentic GenAI QA Platform

Tests That Evolve With Your App and Reveal Your Bugs.

We write your end-to-end suite, run it on every deploy, and repair it as your product changes — while a real regression gets reported, never rewritten. No existing tests required. Standard Playwright specs, in your repo: if you fire us, your suite still runs.

30 minutes, our sandbox or your staging URL. You keep the report. No card, no production access, nothing to install.

No existing tests needed · The specs are yours · Gate starts in report-only · Verify every number yourself

triage-report.json Auto-generated
{ "outcome": "DEFECT_CONFIRMED", "category": "FUNCTIONAL_REGRESSION", "severity": "HIGH", "expected": "Rs. 500", "observed": "Rs. 250", "gate": "BLOCK_DEPLOY" }
Every run  →  Predict · Heal · Hunt · Gate
Three things that decide whether this clears your security review
The interesting part of a self-healing engine is where it stops

It fixes the test, never the verdict.

Four failure types get repaired in the spec. Two — a real regression, a broken fixture — are reported and left alone. The engine is not allowed to rewrite a product signal.

It cannot force a test green.

No loosening an exact match, no downgrading a visibility check. That's a static check on the proposed diff, not a prompt instruction — deterministic rules plus an AST scan, no LLM calls. Two attempts, then it asks a person.

Your code never leaves your infra.

Runs offline on your own runner. Read-only until you say otherwise. Every capability is denied by default and switched on deliberately.

Repairs automatically drifted locators · moved flows · changed copy · timing races
Reports only real regressions · broken fixtures
The Agentic Loop

A ticket in. A deploy verdict out.

One closed loop authors, runs, self-heals, and gates your tests — with guardrails you can prove to leadership.

01
Ticket
Structured intent in
02
Plan
Risk-ranked test plan
03
Generate
Runnable test specs
04
Heal
Auto-repairs broken locators
05
Gate
Proof-backed BLOCK / SHIP
Max 2 heal attempts Never softens a failing test Never learns from guessed passes Deny-by-default scopes Regression memory Live browser automation
Four Pillars. Zero Compromise.

The QA work nobody should be doing by hand — running autonomously

Speed, accuracy, cost, and governance in one agentic platform, not a script library.

Speed

Run only what the change touches. Risk-ranked selection skips the specs your diff can't affect.

Accuracy

Know flake from a real bug. The Execution Judge classifies every failure and shows its reasoning — you review only what it wasn't sure about.

Cost

Maintenance stops being your problem. Drift, moved flows and copy changes are repaired in the spec — and we own the upkeep, not your engineers.

Trust & Governance

It never rewrites a product signal. Guessed passes go to a human and never seed what the engine learns from. Deny-by-default scopes stay enforceable.

The Lifecycle

Predict → Heal → Hunt → Gate

Every run follows the same closed loop — and ends in one deploy verdict you can trust.

01

Predict

The Impact Engine risk-ranks your PR and runs only the flows that matter.

02

Heal

Broken locators are auto-repaired mid-run, then promoted into a selector bank so the next run skips recovery.

03

Hunt

The Bug Hunter separates real behavioral regressions from flaky noise.

04

Gate

You get one proof-backed verdict — SHIP or BLOCK_DEPLOY — with evidence attached.

See It Work

Brittle fail → authored suite → self-heal → Proof Artifact

A 45-second interactive walkthrough of the agentic loop — play, scrub, or jump scenes. Same flow design partners see in the live sandbox demo.

Prefer full screen? Open the walkthrough · Book a live sandbox demo

Live storefront run · 9 engines

Predict → Heal → Hunt → Gate — with on-screen voiceover

Captioned live run against automationexercise.com. Full-screen cards explain each engine (Impact through Governance). Pricing drift is injected on purpose so the gate is visible on a healthy site.

Open captioned player · Executive voiceover script · triage-report.json · Gate: BLOCK_DEPLOY

Proof, Not Promises

Every finding ships as evidence your team can act on

No chat message, no vibes. Each run emits a versioned Proof Artifact — JSON + Markdown — with root cause, severity, and the gate call included.

  • Real output from a sandbox bug-hunt — expected Rs. 500, observed Rs. 250 (drift injected on purpose), caught and blocked.
  • From a ticket to a runnable spec to a gate verdict — authored, run, and blocked automatically.
  • Past regression recalled on a later PR — forced back into the run and blocked again (never shipped twice).
  • Deny-by-default scopes + live browser automation: agents can't soften a failing test, and every action is audited.
triage-report.json Auto-generated
{ "outcome": "DEFECT_CONFIRMED", "category": "FUNCTIONAL_REGRESSION", "severity": "HIGH", "expected": "Rs. 500", "observed": "Rs. 250", "gate": "BLOCK_DEPLOY" }
Real output from a sandbox bug-hunt. Root cause, severity, and gate call included — the evidence your team acts on. The Rs. 500 → Rs. 250 drift was injected on purpose so the gate is visible on a healthy site; the detection, heals and verdict are unscripted.
Latest sandbox run · 1 defect caught · 0 shipped · 2 selectors self-healed · selector bank advisory
Measured, and Not

What we've measured — and what we haven't

The failure mode that matters isn't accuracy in aggregate. It's which way the misses go.

Measured

  • Zero real regressions missed. On 37 hand-labelled failures, all 7 genuine bugs were caught — that's the error class we treat as unacceptable.
  • 4 misses, all in the safe direction. False positives escalated for review. Cost: a triage hour, never a shipped bug.
  • Labelled by hand, not by the model it grades. The set is frozen; the per-class breakdown, the four misses and the run history are published on the evidence page, with the judge and engine commit that produced them.

Not yet

  • No production deployment. Verified in our sandbox, not on a live pipeline — which is exactly why the gate starts in report-only.
  • n=37 is small. It grows from every triaged run; the set stays frozen so the score remains comparable.
  • No customer case study. That's precisely what the design-partner rate buys.
Under the Hood

Nine specialized engines, one agentic platform

Not a script library — a coordinated system where each engine owns one job.

01ImpactRisk-ranked selection (e.g. 3 of 20)
02Regression MemoryRecalls past hotfixes so they can't ship twice
03Self-HealingGuardrailed repair · selector bank · Tier-0 flywheel
04Bug HunterCatches behavioral regressions
05Proof ArtifactsEvidence for every finding
06Quality GateTests mapped to requirements
07Ticket-to-GateTicket → runnable spec → gate
08Sprint TrendFlags chronic, deferred fixes
09GovernanceExecution Judge · offline triage · deny-by-default scopes
Want this packaged and priced?
The DeployShield Suite — the same engine delivered as a managed service, with a green-build guarantee on covered flows (Terms), from $3,540/mo.
Explore the DeployShield Suite →

See it catch a real bug in 30 minutes.

We run the full loop against our sandbox — or point it at your staging URL and show you your own app. You keep the report either way. No credit card, no production access, nothing to install.