Frequently asked
questions.

QA-focused testing is specifically designed to mirror how a real user interacts with software, prioritizing the end-user experience over the underlying code logic. Unlike traditional unit or integration tests that verify internal code behaviors, QA-focused tests identify usability issues, broken user flows, and UI regressions that directly affect your users. This makes it an essential layer of your testing strategy, especially as AI-generated code becomes more prevalent and the surface area for unexpected behaviors expands.

Testomniac is ideal for software engineering teams that are using AI coding agents (like Cursor, Copilot, or Claude) to accelerate development and need a reliable way to catch regressions without dedicated QA headcount. It's especially valuable for early-stage startups, fast-moving product teams, and any engineering organization where the cost of usability regressions is high but dedicated QA resources are limited.

Testomniac focuses on front-end, user-facing functional testing. This includes end-to-end workflow testing (simulating full user journeys), regression testing (catching changes that break existing functionality), and usability validation for key user flows like authentication, navigation, form submissions, and checkout sequences. It is not designed for unit testing, API testing, or performance/load testing.

On the initial scan, Testomniac uses AI to explore your application, map out its structure, and identify key user workflows. It then builds a test library around those workflows based on what it discovers. In subsequent runs, it leverages that stored knowledge base rather than re-exploring from scratch, saving time and token costs while maintaining deep product context. You can also provide hints or context about your application to guide the initial discovery process.

Yes. Testomniac is purpose-built for front-end, user-facing web application testing. It is not designed for backend API testing, unit testing, load/performance testing, or native mobile applications. It also requires that the application under test be accessible via a URL; it cannot test applications that require complex infrastructure setup or that run exclusively in private, non-routable network environments without additional configuration.

Testomniac integrates with the project management and source control tools your team already uses. Currently supported integrations include Jira, Linear, GitHub Issues, and GitHub. When Testomniac detects a regression or failure, it can automatically create and assign tickets in your chosen tool, complete with screenshots and reproduction steps, so nothing falls through the cracks.

Testomniac uses a two-phase model. In the first phase, test creation, AI explores your application and writes test scripts. This is where AI inference and tokens are consumed. In the second phase, ongoing test execution, those scripts run as traditional automated tests with no AI involvement. This means your daily or CI/CD-triggered regression runs are completely token-free. AI is only re-engaged when new features are detected or tests need to be updated after a significant product change.

Because execution doesn't need it. Once a test has been written and validated, re-running it with AI adds cost and latency without adding value. Traditional test automation scripts are deterministic, fast, and cheap to run. By separating the intelligence layer (test creation) from the execution layer (test running), Testomniac gives you the benefits of AI-powered test authoring with the efficiency of conventional test runners. The result is a system that scales economically as your test suite grows.