We build AI testing systems that generate test cases, identify bugs, predict failure points, and improve test coverage beyond what manual QA can achieve.
Traditional QA processes struggle to keep pace with modern development velocity. Manual test writing is slow, test maintenance is burdensome, and coverage gaps persist despite significant investment. AI-powered testing transforms this equation by automating test generation, intelligently prioritizing test execution, predicting which code changes are most likely to introduce bugs, and identifying test gaps that manual processes miss.
AI does not replace human QA engineers; it amplifies their effectiveness. AI handles the repetitive work of generating test cases for edge cases and boundary conditions, freeing QA engineers to focus on exploratory testing, user experience evaluation, and test strategy. The combination of AI efficiency and human creativity produces better software quality than either approach alone.
Arthiq builds AI testing tools tailored to your technology stack, application architecture, and quality standards. Our solutions integrate with your existing CI/CD pipeline and testing frameworks, augmenting your current QA process rather than requiring a wholesale replacement.
Writing comprehensive test cases is one of the most time-consuming aspects of QA. Arthiq builds systems that automatically generate test cases from code, specifications, and API definitions. For API testing, we analyze endpoint definitions and generate test cases covering valid inputs, boundary conditions, error cases, and security scenarios. For UI testing, we analyze application screens and generate interaction sequences that cover critical user flows.
Our test generation goes beyond simple parameter variation. We use LLMs to understand the business logic being tested and generate test cases that exercise meaningful scenarios. For a payment processing system, the generated tests would cover not just valid and invalid amounts but scenarios like partial refunds, currency conversions, concurrent transactions, and timeout handling.
Generated tests are presented for review and approval, ensuring your team maintains control over what gets tested. Approved tests are integrated into your test suite and run automatically in CI/CD. The generation system learns from your review feedback, improving the relevance of future generated tests.
Running the entire test suite for every code change is often impractical due to time constraints. Arthiq builds test intelligence systems that analyze code changes and predict which tests are most likely to catch regressions. High-risk tests run first, and the test execution order is optimized to find failures as early as possible.
Our prioritization models consider code change analysis (which modules were modified and what tests cover those modules), historical failure correlation (which tests have found bugs in similar changes), and risk assessment (which areas of the application are most prone to regressions). The result is a test selection that catches the same number of bugs in a fraction of the execution time.
For flaky test detection, our systems identify tests that produce inconsistent results and diagnose the root causes: timing dependencies, test environment issues, or genuine intermittent bugs. Flaky tests are quarantined and fixed, improving the reliability of your test suite and the trust your team places in test results.
Visual regressions, unintended changes to the appearance of your application, are difficult to catch with traditional functional tests. Arthiq implements AI-powered visual testing that compares screenshots across builds and intelligently identifies meaningful visual changes while ignoring irrelevant variations like animation states, dynamic content, and rendering differences.
Unlike pixel-diff tools that produce excessive false positives, our visual testing uses computer vision models that understand layout structure and visual significance. A shifted button or changed font is flagged as a potential regression. Dynamic content like timestamps or user data is recognized as expected variation. This intelligent filtering makes visual testing practical for regular use.
For applications with complex visual states, we generate visual test scenarios that cover responsive breakpoints, dark and light modes, different content lengths, and error states. This comprehensive visual coverage catches the rendering issues that slip through functional testing.
AI-powered testing is a force multiplier for your QA team. Arthiq builds testing tools that integrate seamlessly with your existing development workflow, augmenting your team capabilities rather than disrupting established processes.
We deliver testing solutions in phases, starting with the highest-impact capability for your situation. For teams with coverage gaps, we start with test generation. For teams with slow test suites, we start with intelligent test selection. The approach is tailored to your specific quality challenges.
Contact us at founders@arthiq.co to discuss how AI can improve your software quality and accelerate your QA processes.
Our team will build AI testing tools that generate better tests, run them smarter, and catch bugs faster, all integrated into your existing development workflow.