Tshabok AI

Tshabok AI generates test cases from uploaded documentation or directly from a product URL, then lets QA teams review and export them. It targets small and mid-sized development teams that want fast first-draft coverage without adopting a full test management suite.

Tshabok AI is a QA automation service built around one job: turning project documentation into structured test cases. Teams that already maintain user stories or specifications upload those files, and the platform analyses the requirements and returns a set of test cases that cover the stated behaviour along with the edge cases a manual author might overlook. The pitch is speed of coverage rather than test execution, so the output is a document your QA team reviews and imports into its own tooling. There is a second path for projects with thin or missing documentation. In that mode you submit a URL, and the AI works from the live product surface to derive documentation first and test cases second. That makes the tool usable during early discovery or on inherited codebases where nobody wrote requirements down, though the resulting cases will only be as good as what the crawler can observe. Both paths sit behind a subscription, and the vendor claims time savings of roughly 80 percent on test case creation against manual authoring. The workflow is deliberately linear. Upload or generate documentation, let the analysis run, review the generated cases, adjust anything that reads wrong, then export to your preferred test management tool. Regeneration is supported, so when requirements shift you can re-run the process instead of patching cases by hand. Tshabok positions this alongside a free website health checker that scans for broken links and missing images, which suggests the product family targets small and mid-sized development teams that want broad QA hygiene without a dedicated toolchain. The honest framing is that Tshabok competes with AI features bolted onto established test management suites. What it offers instead is a standalone, low-ceremony pipeline that starts from documentation or a URL rather than from an existing test repository. Teams that already live inside a large platform may find the export step redundant. Teams without one get a faster route from requirements to a first draft of coverage. The site quotes 5K+ users and 95 percent requirement coverage accuracy, figures the vendor supplies without published methodology.