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QAEverest AI
AI-Powered QA Platform for Smarter Software Testing
our automated tests break every release and QA drowns in maintenance. QAEverest turns a plain-English user story into complete test cases, then executes them across web, mobile, API, performance, security and accessibility — and repairs them itself when the app changes. Time-travel replay pinpoints root cause, PR bots score release risk, and an AI copilot drives it all from chat or your IDE. Stop rewriting broken tests. Ship with a suite you can actually trust.
Hey Product Hunt 👋
I've spent years around QA teams, and the same thing kept happening: a team invests months building an automation suite, then a button moves and half of it goes red. None of it is a real bug. Studies put 30–50% of QA effort into maintenance — not new coverage — and eventually the suite gets ignored, manual regression comes back, and real bugs slip to production.
So we built QAEverest around that problem rather than around test generation. It crawls your app, diffs what changed, and auto-repairs the affected tests — then tells you what actually broke versus what just moved. Generation from a plain-English user story is the on-ramp; self-maintenance is the point.
Around that core we added the things you need once your suite is trustworthy: execution across web, mobile, API, performance, security and accessibility; time-travel replay that captures console and network traces so you can scrub back to the moment of failure; a PR bot that scores release risk and picks the tests worth running; and an MCP server so you can drive it from Claude Code, Cursor or VS Code without leaving your editor.
We're looking for teams buried in flaky Selenium/Cypress/Playwright suites — that's who this is for. Tell me what breaks in your suite most often, I'll be here all day.
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About QAEverest AI on Product Hunt
“AI-Powered QA Platform for Smarter Software Testing”
QAEverest AI was submitted on Product Hunt and earned 2 upvotes and 1 comments, placing #146 on the daily leaderboard. our automated tests break every release and QA drowns in maintenance. QAEverest turns a plain-English user story into complete test cases, then executes them across web, mobile, API, performance, security and accessibility — and repairs them itself when the app changes. Time-travel replay pinpoints root cause, PR bots score release risk, and an AI copilot drives it all from chat or your IDE. Stop rewriting broken tests. Ship with a suite you can actually trust.
QAEverest AI was featured in API (98.6k followers), Software Engineering (43k followers) and Artificial Intelligence (478.1k followers) on Product Hunt. Together, these topics include over 139k products, making this a competitive space to launch in.
Who hunted QAEverest AI?
QAEverest AI was hunted by Rupesh Kabra. 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.
Want to see how QAEverest AI stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Rupesh Kabra