Autonomous AI QA

Find real bugsbefore your users do.

AISwarmQA explores your app like a user, captures evidence like an engineer, and opens the GitHub issue before your team even knows to look.

Start free audit Watch it find a bug →

your-app.com/sign-in

Critical finding

Forgot password link does not respond

The link renders, but no click handler is wired to it. Nothing happens on click — no navigation, no request, no console error. Reproduced on 3 of 3 attempts.

 function ForgotPasswordLink() {
−  return <button type="button">Forgot password?</button>;
+  return <button type="button" onClick={openResetFlow}>Forgot password?</button>;
 }

Route — /sign-inConfidence — 0.94

DevelopersSaaS teamsStartup foundersQA engineersGitHub IssuesPlaywright workers

Why it matters

Your users should not be your first QA signal.

Manual QA is slow, browser bugs are hard to reproduce, and thin bug reports rarely become actionable engineering work.

Users find broken flows first
Manual checks miss edge states
Evidence disappears during triage
Findings stall before GitHub

How it works

A clear path from URL to issue.

Every step is bounded, visible, and structured for engineering review.

Enter a URL

Point AISwarmQA at any staging or production route.

Swarm agents deploy

Explorer, analyst, and reporter agents split the work.

Browser actions

Agents click, type, and navigate real flows like a user would.

Finding surfaces

A concrete bug is isolated with severity and confidence.

Evidence captured

Screenshot, console trace, and reproduction steps attach.

GitHub Issue

Confirm once, export a structured, ready-to-fix issue.

Interactive demo

Watch a finding become engineering work.

A deterministic public simulation. It does not submit visitor URLs to the production audit queue.

Ready to scan0%

Swarm agents

Waiting to start.

Agent #1 — Explorer

Crawls the target, clicks through real flows, and fills forms to discover every reachable page and control.

Agent #3 — Analyst

Inspects runtime behavior — console errors, network failures, layout shifts — across desktop and mobile viewports.

Agent #7 — Reporter

Captures evidence, normalizes the finding into severity and repro steps, and prepares it for GitHub export.

Browser sessionFinding & evidenceGitHub issue

/checkout

This is a deterministic public demo. It does not submit visitor URLs to the production audit queue.

Product power

The useful parts of QA automation, wired together.

Discovery, evidence, workspace safety, billing limits, and export history live in one product flow.

Autonomous browser agents

Explore flows, click controls, inspect runtime signals, and stay inside safety bounds.

Evidence capture

Attach screenshots, affected routes, state, and durable evidence links to findings.

GitHub Issue export

Turn selected findings into structured, ready-to-fix GitHub Issues after confirmation.

Workspace controls

Keep audits, repositories, export batches, and evidence scoped to authorized workspaces.

Audit history

Track normalized findings, severity, confidence, duplicate state, and export status.

Content clarity

Public docs, glossary, and SEO architecture explain the product without hidden crawler tricks.

GitHub transformation

The strongest bug report is a packet of context, not a complaint.

Every finding carries enough signal for engineering to reproduce, prioritize, fix, and verify — before it ever reaches GitHub.

1Finding
2Evidence
3Repro steps
4Expected vs actual
5Suggested fix
6Acceptance criteria
7GitHub Issue

Product UI

Built around the real audit lifecycle.

Preview data mirrors real objects: audits, findings, evidence, exports, plans, and workspaces.

12Audits this month

7Open findings

3GitHub issues exported

criticalCheckout button does not complete/checkout

highMobile menu traps keyboard focus/pricing

mediumDocs link returns HTTP 404/docs/getting-started

Evidence stays private and durable.

Stable evidence routes, private storage, revocation, workspace authorization, and retention policies keep bug context useful without exposing raw storage URLs.

Dashboard signals stay realistic.

Recent audits, severity summary, scan progress, GitHub exports, duplicate state, and plan usage match the actual AISwarmQA data model.

Pricing

Start free. Upgrade when QA becomes a release habit.

The Pro yearly price is exactly 10 monthly payments: $790/year saves $158 compared with twelve $79 monthly payments.

Free

$0/forever

2 audits/month
25 pages/audit
1 concurrent audit
GitHub export
7-day evidence retention

Start free audit

Pro

$79/month

50 audits/month
500 pages/audit
3 concurrent audits
90-day retention
Email reports
Priority queue
$790/year saves $158

Start Pro

Business

Custom/year

Configurable usage
Extended retention
Team and role controls
Priority support
Future API access

Contact sales

Built for

No fake logos. Just the teams this is made for.

Developers, founders, QA engineers, agencies, and SaaS teams that need bug reports with proof.

Solo founders validating launches
Developers preparing releases
QA engineers improving triage
Agencies checking client sites

What's next

Where AISwarmQA is headed.

Shipped features above are live today. These are directions we're building toward next.

Coming soon

Load-swarm simulation

Simulate concurrent user traffic at scale to surface issues that only appear under real load.

Coming soon

Database integrity checks

Catch data consistency issues that only surface after sustained, high-volume usage.

Coming soon

Scheduled recurring audits

Run audits automatically on a schedule and get alerted only when something regresses.

Coming soon

Slack and Jira export

Route confirmed findings straight into the tools your team already triages work in.

FAQ

Answers before your first audit.

Visible content only. The FAQ schema mirrors these exact questions.

01What does AISwarmQA test?

AISwarmQA tests authorized web application flows through browser exploration, interaction checks, runtime observations, mobile states, accessibility signals, links, and forms.

02Does it replace human QA?

No. It reduces repetitive discovery and evidence gathering so humans can review, prioritize, and decide what to fix.

03Does it work with authenticated applications?

Authenticated testing is supported through controlled setup flows and workspace authorization, not uncontrolled public URL submission.

04Does it modify my site?

No. A built-in safety policy blocks destructive actions before they run — deletions, payments, logout, and account changes are rejected automatically, every audit.

05How does GitHub export work?

A user selects a finding, previews the issue, chooses an authorized repository, confirms export, and AISwarmQA stores the export record.

06What evidence is stored?

Evidence can include screenshots, affected pages, route metadata, and stable evidence IDs served through AISwarmQA routes.

07Is the audit safe?

The pipeline uses bounded missions, timeouts, budget checks, workspace authorization, and deterministic fallback.

08How many pages are scanned?

AISwarmQA discovers same-origin pages via sitemap.xml or a bounded crawl. Free includes 25 pages per audit, Pro includes 500. Business usage is configurable on request.

09Can I cancel an audit?

Yes. Audit cancellation is part of the application workflow.

10Can my team use one workspace?

Yes. Team workspace controls and invitations are part of the SaaS foundation.

11What happens to evidence after retention expires?

It's deleted from storage automatically on a recurring schedule — 7 days on Free, 90 on Pro, 365 on Business — not just hidden from view.

Run your first autonomous QA audit.

Find the bug, keep the proof, and turn it into work your team can fix.

Start free audit View sample report