Buglab – Spellcheck for UI

Hacker News

Hey HN, We wanted to get your thoughts and feedback on a software development tool we recently released. Buglab is a visual testing tools for websites and web apps. It works by running automated scheduled tests that compare every page to its baseline and notifies you in case there are any discrepancies. That means you can use it both for monitoring that nothing on your product has broken (which could be caused by internal updates or external libraries, APIs, etc.) or for A/B testing to ensure consistency across browsers. It's like a spellchecker for your UI and UX. Our goal is to eliminate the repetitive and labour intensive testing procedures that so many companies do in their product development cycles and free those humans to do more productive tasks. Buglab’s big advantage is that it tests the fully-rendered end result of the product, not just its code. And another nice benefit is that it can be set-up and used by non-technical people in a matter of minutes. Please use the link below to set-up an account. It will be credited with 250 free screens to test, but don’t hesitate to contact me in order to get more if you want to test more. My email is my username @buglab.ai. https://buglab.ai/platforms/user/register.html Looking forward to hearing your feedback.

Visit product View on Hacker NewsApr 25, 2024

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Product HuntOn track for Day 1 leaderboard · Strong signals: apps, user, email · Missing: mac, agents, macos

93%93% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

68%68% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Missing: https docs, excited, just released

53%53% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Strong signals: apps · Missing: mobile apps, ios, personal

45%45% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: platform · Missing: plus, intuitive, reviews

33%33% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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