Agentic QA for teams shipping complex products
An independent AI agent tests your app like a user — no scripts, no selectors, no test code to maintain. We set it up with you; your team reviews findings, not flaky tests.
Point it at your app
Give it a URL — cover the whole product, or target the flows your team just shipped.
The agent tests it like a user
It navigates your app and checks every interaction — no scripts to write, no selectors to maintain.
Get evidence your team can act on
Structured bug reports with video, screenshots, and step-by-step reproduction.
Point it at your app
Give it a URL — cover the whole product, or target the flows your team just shipped.
The agent tests it like a user
It navigates your app and checks every interaction — no scripts to write, no selectors to maintain.
Get evidence your team can act on
Structured bug reports with video, screenshots, and step-by-step reproduction.
Enterprise-grade by design
Independent QA that respects your stack, your secrets, and your source code.
Local-first
Tests run fully on your machine with your own Gemini key — localhost targets, no tunnels, no source-code upload.
Credentials the model never sees
Credentials are AES-256-GCM encrypted; the agent types them by name, so their values never enter the model context.
Independent by design
Tests from the outside, like a real user — no repo integration, no code upload required. Verification stays independent of the code that wrote the feature.
CI-native
A CI-grade CLI with service-key auth, JSON output, exit codes, and auto-detection for GitHub Actions, GitLab, CircleCI, and Buildkite.
Video evidence for every bug
Every run is recorded on video and each bug ships with screenshots and step-by-step reproduction — proof, not just a claim.
Coverage without maintenance
Tests your real UI — not DOM or selectors. Catches regressions across real user flows, with no test code for your team to maintain.
Nothing to set up
Point at any URL and start testing. Web, localhost — no CI/CD pipeline or configuration required.
Secure by default
Credentials are encrypted and the agent types them by name, never seeing their values. No source code access required.
Coverage without maintenance
Tests your real UI — not DOM or selectors. Catches regressions across real user flows, with no test code for your team to maintain.
Nothing to set up
Point at any URL and start testing. Web, localhost — no CI/CD pipeline or configuration required.
Secure by default
Credentials are encrypted and the agent types them by name, never seeing their values. No source code access required.
Runs where your team works
Test localhost, staging, or production locally with your own key — only model-provider calls leave your network.
Or run in the cloud, in parallel, from any browser with Agentiqa Web.
Ways to use Agentiqa
Fits the way your team already ships.
CLI
A quality gate for your CI/CD pipeline.
- GitHub Actions, GitLab, CircleCI, Buildkite
- Service-key auth, JSON output, exit codes
- Claude Code / Cursor / Codex plugins
Web
Cloud runs for your whole team, no setup needed.
- Cloud execution, nothing to install
- Parallel test-plan runs
- Learns your app across runs
- Shared access across your team
Desktop App
Local-first evaluation on your own machine.
- Test localhost & internal builds
- Bring your own key — your app and data stay on your machine; only model calls go out
- Always free on Community Plan
What is agentic testing?
AI agents execute testing goals and surface findings — not just scripted steps.
What kind of issues does it catch?
Functional and UX regressions — broken states, visual glitches, responsive problems — each reported with severity, category, and step-by-step reproduction your team can act on.
How does onboarding work?
Team plans include a warm start: we set up and maintain your suite with you for the first month, then any engineer or QA runs it.
Can we run it locally and in our CI?
Yes — run local-first for localhost and internal builds, or wire the CI-grade CLI into GitHub Actions, GitLab, CircleCI, or Buildkite.
How does it protect our code and secrets?
No source code access required; credentials are encrypted and never sent to the LLM.
How is it different from AI + browser?
For a one-off check, that works. It stops working when testing must repeat and be trusted: a raw prompt loop wanders, reports "looks fine" without proof, and reads your passwords. Agentiqa is that idea built into a QA system — supervised runs, recorded step-by-step evidence, plans that re-run in CI and in parallel, credentials the model never sees, and testing context that compounds.
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hi@agentiqa.com© 2026 Agentiqa, Inc. All rights reserved.