Introducing AIQA: AI-Powered QA for Mobile & Web

Why traditional QA becomes a bottleneck

Manual regression testing is valuable, but repeatedly walking through every screen consumes the time of engineers, designers, and QA specialists. Scripted automation helps predictable flows, yet every script becomes another asset that must be written and maintained.

AIQA starts from the product itself. Give it an APK, a zipped Runner.app simulator build, or a web URL. The crawler explores reachable screens and captures evidence without requiring a team to describe every click first.

One crawl, several perspectives

A product can be technically functional and still feel broken. That is why AIQA separates complementary test scopes.

• —Design testing compares captured screens with Figma references and highlights visual differences.
• —Logic testing reviews flows, state, and behaviour for functional inconsistencies.
• —Marketing testing evaluates clarity, calls to action, copy, trust, value, and friction from a user's perspective.
• —Full testing combines design, logic, and marketing review in one run.

Results built for action

Each finding includes a screenshot, severity, description, and supporting metadata. Teams can inspect results in AIQA, export structured JSON, or send selected bugs to Jira when their plan includes the integration.

The goal is not to replace thoughtful human QA. It is to automate repetitive exploration and first-pass review so people can focus on risk, product judgement, and the hard edge cases.

Start with the build you already have

Create a project, choose a platform and test scope, upload the build or enter a URL, and start a run. Figma is optional: connect it for design comparison, or use logic and marketing modes without it.

AIQA makes broad product checks available earlier in the release cycle, when defects are cheaper to understand and fix.