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AI Usability Test Agent That Thinks and Acts Like Human

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AI Usability Test Agent That Thinks and Acts Like Human

I'm Sayuj, and I built Zero Touch, an AI usability agent that interacts with websites through the GUI (Graphical User Interface), just like a real human would. Unlike traditional tools that rely on the DOM, this AI clicks, scrolls, and navigates exactly how users do, without touching the underlying HTML. I built this as a fun side project to simplify usability testing for landing pages and websites. It’s completely free to use right now, and I’d love to get your feedback or ideas for improvement!

Visit productView on Hacker NewsJan 15, 2025
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Actual performance

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: agent, user · Missing: mac, agents, macos
91%91% 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
52%52% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
52%52% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Strong signals: interface, users · Missing: plus, platform, intuitive
42%42% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: users · Missing: mobile apps, ios, personal
34%34% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
20%20% 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.

Incorrect prediction on native model

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