Manual test case design is one of the biggest bottlenecks in modern QA, consuming 30-40% of total QA effort per release. It delays downstream testing, pushes defect discovery late in the cycle, and leads to release delays and defect leakage. This whitepaper looks at how AI-powered test case generation can remove that bottleneck, and why Qualitrix chose Nogrunt, an AI engine that turns structured and unstructured requirements into traceable test cases for expert review.
In a controlled comparison against manual authoring, Nogrunt designed 1,141 test cases against 485, cut design time from 114 hours to 7 (a 94% reduction), and reduced total effort by 59%. Coverage more than doubled, including edge cases and redundancy detection. The paper is also open about the trade-offs: initial accuracy was 74% against 92% for manual work, and review effort rose at first, but results improved sprint by sprint as the AI learned from feedback.
Download the Full Whitepaper
Want to see the complete picture? Get the full whitepaper for the detailed benchmark data, the learning curve behind the numbers, and the enterprise risk and mitigation playbook. It also includes a practical 3-phase roadmap (Pilot, Scale, Optimize) for adopting AI-powered test automation. Download it now to see how your QA team can cut manual effort, improve coverage, and deliver faster, more predictable releases.