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Kanten
Turn requirements into reviewable, traceable test cases
Kanten helps QA teams turn requirements into reviewable, traceable test cases. Maintain a shared library of testing perspectives, such as boundaries, permissions, and unstable networks, and apply the relevant ones to each function. Design cases manually or with AI assistance, then review, edit, and export them. Available in English and Japanese.
Hi Product Hunt! I’m Nico, a QA engineer and the creator of Kanten.
After years in QA engineering and team leadership, one question keeps coming up: how do we know we’ve considered the right risks before writing test cases?
Kanten is inspired by viewpoint-driven testing approaches I explored in Japanese testing resources. The idea is to maintain reusable testing perspectives, such as boundary values, permissions, state transitions, and unstable networks, then apply the relevant ones to each function.
For example, “unstable network” is a shared perspective. Applied to saving a draft, it becomes concrete: if the connection drops, are the edits preserved, is the failure clear, and can the user retry?
Kanten brings this into a workflow: • Break requirements into reviewable functions. • Decide which testing perspectives apply. • Design traceable cases manually or with AI assistance. • Review, edit, and export the results.
AI drafts suggestions; QA decides what applies and what is ready.
You can try it with 100 one-time AI credits after email verification. Manual editing and export are free. English and Japanese interfaces are available.
I’d love feedback from QA engineers and leads: try one small, anonymised feature and tell me where the workflow is unclear or the coverage falls short.
How does your team review test coverage today?
About Kanten on Product Hunt
“Turn requirements into reviewable, traceable test cases”
Kanten was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #135 on the daily leaderboard. Kanten helps QA teams turn requirements into reviewable, traceable test cases. Maintain a shared library of testing perspectives, such as boundaries, permissions, and unstable networks, and apply the relevant ones to each function. Design cases manually or with AI assistance, then review, edit, and export them. Available in English and Japanese.
On the analytics side, Kanten competes within Productivity, Developer Tools and Artificial Intelligence — topics that collectively have 1.7M followers on Product Hunt. The dashboard above tracks how Kanten performed against the three products that launched closest to it on the same day.
Who hunted Kanten?
Kanten was hunted by Nico Chen Huibo. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of Kanten including community comment highlights and product details, visit the product overview.
Nico Chen Huibo
Hi Product Hunt! I’m Nico, a QA engineer and the creator of Kanten.
After years in QA engineering and team leadership, one question keeps coming up: how do we know we’ve considered the right risks before writing test cases?
Kanten is inspired by viewpoint-driven testing approaches I explored in Japanese testing resources. The idea is to maintain reusable testing perspectives, such as boundary values, permissions, state transitions, and unstable networks, then apply the relevant ones to each function.
For example, “unstable network” is a shared perspective. Applied to saving a draft, it becomes concrete: if the connection drops, are the edits preserved, is the failure clear, and can the user retry?
Kanten brings this into a workflow:
• Break requirements into reviewable functions.
• Decide which testing perspectives apply.
• Design traceable cases manually or with AI assistance.
• Review, edit, and export the results.
AI drafts suggestions; QA decides what applies and what is ready.
You can try it with 100 one-time AI credits after email verification. Manual editing and export are free. English and Japanese interfaces are available.
I’d love feedback from QA engineers and leads: try one small, anonymised feature and tell me where the workflow is unclear or the coverage falls short.
How does your team review test coverage today?