Krish ChelikavadaJina is your AI QA engineer that tests apps end-to-end and catches bugs autonomously, at scale. It understands UI, code, and user intent. Doesn't rely on test scripts or CSS selectors and requires no maintenance.
Top comment
We built Jina because QA today is broken. Testing hasn’t evolved much in years—teams still rely on scripts tied to CSS selectors and brittle assumptions about UI structure. Even “AI-powered” tools just generate those same scripts faster, which means they still break and still need constant upkeep. Jina takes a fundamentally different approach. It uses browser agents and a vision-first model to interact with your app like a real user would. No selectors, no scripts. Just a goal like “book a flight” or “checkout a cart.” Jina explores the UI, runs the flow, and flags real bugs. When the UI changes, it adapts. It also auto-generates new tests from live user analytics—so as your product evolves, your test coverage does too. The teams behind some of the most iconic ecommerce brands are already using Jina to catch bugs before customers do—and free up engineers to focus on shipping, not debugging tests. Excited to show you what we’ve been working on.
Comment highlights
Just gave Jina’s AI Landing Page Roaster a spin on our homepage draft an I really like how the “friendly roast” format mixes tough-love copy critiques with concrete, line-by-line fixes. It feels like having a seasoned CRO consultant in my browser, minus the invoice. 🔝
A few thoughts as I digest the feedback:
Priority heat map: a quick “high/medium/low” impact tag on each suggestion would help teams tackle the biggest conversion leaks first.
Competitor lens: pulling in a side-by-side snapshot of two competitor pages (with the same roast criteria) could make the insights even more actionable for positioning.
Version tracker: after revisions, re-roasting and seeing an overall score delta (+12% clarity, +8% trust) would turn iterative copywork into a mini-game.
One-click share: a public link that shows the roast report (read-only) would simplify hand-offs to designers or founders who “just want the highlights”, I think.
Overall, I'm really impressed by the mix of tone, clarity, and humor (enough to keep me engaged without sugar-coating the flaws). Great launch! 🚀
Yes, more is needed in the testing space especially using AI! Glad that you picked it up! I think that bug prediction through looking at the code is something AI should be able to do well if given business context!
Very cool launch! Jina feels like the QA teammate every dev team wishes they had — smart enough to understand the app like a user, and hands-off when it comes to maintenance. Excited to see how it reshapes testing workflows!
About Jina on Product Hunt
“AI QA Engineer”
Jina launched on Product Hunt on June 10th, 2025 and earned 148 upvotes and 8 comments, placing #15 on the daily leaderboard. Jina is your AI QA engineer that tests apps end-to-end and catches bugs autonomously, at scale. It understands UI, code, and user intent. Doesn't rely on test scripts or CSS selectors and requires no maintenance.
Jina was featured in Software Engineering (42.5k followers) and Artificial Intelligence (469k followers) on Product Hunt. Together, these topics include over 100.8k products, making this a competitive space to launch in.
Who hunted Jina?
Jina was hunted by Krish Chelikavada. 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.
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