AI-Powered Test Case Generation with QA flow

QA flow transforms the test case creation process by generating detailed, structured test cases directly from design assets and user stories. By reducing manual effort, it allows QA teams to focus on deeper analysis, collaboration, and improving overall product quality

Disha

Preparing test cases as soon as we get the user stories is part of the QA process. We analyze the impact areas, prepare test scenarios, and evaluate the effectiveness of the new functionality. The core idea in preparation of test cases is to cover the new feature and then let’s spend time analyzing how this new functionality/ feature impacts the existing functionality - regression to be specific. In my own experience, I have spent time in creating test cases for the new functionality and then analyzing the impact areas. With QA flow, I can submit the initial part and then spend the rest of my hours with the QA team reviewing the test cases created by QA flow and and brainstorming on other areas.

How does QA flow generate test cases ?

  1. Design assets
    Simply upload your design assets—Figma files, mockups, or screenshots of the feature you want to test. QA flow analyzes these visuals to automatically generate relevant test cases, ready for review and execution within minutes. This streamlines early-stage testing and ensures alignment between design intent and functionality. Take a look at how you can generate test cases using design assets
  2. User Stories
    Have your requirements documented in Linear or Jira? Simply upload the PDF to QA flow and hit Generate. Within minutes, the agent turns those user stories into structured, actionable test cases. No more manual drafting or missed edge cases — just fast, consistent, and comprehensive test coverage ready to review. Take a look at how you can generate test cases using user stories
  1. or Add both
    For the most comprehensive coverage, you can combine design assets and user stories in QA flow. By doing so, the platform generates richer, more contextual test cases — ensuring every interaction, flow, and detail is captured.
  2. Provide additional context
    This section is key, it helps the AI focus on edge cases and tailor the generated test scenarios accordingly. The more detailed you are here, the better the results. Include any extra information, conditions, or notes you’d like the agent to consider when creating your test cases.

    With less manual effort spent writing tests, QA teams can redirect their focus toward peer reviews, collaboration, and refining quality strategies that truly move the needle.

Interested in learning more?

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