Introduction
Agentiqa is an AI QA engineer for web apps — it explores your app in a real browser, proposes what to test, finds bugs, and reports them with evidence.
Agentiqa is an AI-powered testing platform for web applications. An LLM agent navigates a real browser, discovers what matters, executes test plans, and reports issues with screenshots and reproduction steps.
The model: the agent proposes, you curate
You provide a URL. The agent provides everything else — what to test, why it matters, how to test it, and what looks broken. Your role is to approve, reject, or redirect at three checkpoints:
- Scope — the areas the agent discovered, ranked by risk. Default: approve all.
- Plan — how each area will be tested. Default: approve all.
- Findings — bugs with evidence and repro steps. The only step that always needs your review.
In headless contexts (CLI, CI, scheduled runs) every checkpoint auto-approves and the agent uses its own judgment — same engine, same quality, no human in the loop.
Where you run it
| Surface | Best for | Guide |
|---|---|---|
| Web app | Trying Agentiqa in the browser, cloud execution | Web App |
| Desktop app | The full experience with a built-in headed browser | Desktop App |
| CLI | Local runs and scripting (agentiqa explore / agentiqa run) | CLI |
| Coding agent | Authoring and running plans from Claude Code, Cursor, or Codex | Agent skill |
| GitHub Action | Running saved plans in CI and gating on the result | GitHub Action |
The web and desktop apps share the same feature set — the difference is a small set of platform capabilities. See Desktop vs Web.
Next steps
- New here? Start with the Quickstart.
- Automating in CI? Read CI Integration for the exit-code contract and JSON envelope.
- For agents: this site serves
/llms.txtand/llms-full.txt, and every page has a.mdvariant (append.mdto any docs URL).