We've built a flirting AI: no sign-ups, no hassle, just Matches

Hacker News

I’ve never been a natural at the dating game, often seeking advice from friends who just seemed to get it. That's why a friend and I developed Hazel AI for people like me. It's like having that savvy friend in your Telegram (and soon WhatsApp) who's always there to give you a second opinion on conversations and profiles. We also want to try to counter the current culture of cluttered apps that trap you in subscription mazes and use dark patterns to keep you hooked: - Instant Chatting: Start chatting with Hazel on Telegram right away—no need to sign up. - Free to Try: Dive in without any credit card hassle, and see if it’s for you first. - Easy Opt-Out: A simple command in Telegram lets you unsubscribe anytime. - Weekly payment schedule: Maximum flexibility for the user But Hazel isn't just about clever lines—it's built to offer thoughtful, friend-like advice. Whether it’s figuring out when to move on from a chat or getting feedback on your approach, Hazel aims to be a supportive and genuine companion. But boy does it generate clever lines as well! We’d love to hear your feedback—good or bad. No ego here, just tell it like it is :)

Visit product View on Hacker NewsApr 30, 2024

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Actual performance

5points

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Launch Intel predictions

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

68%68% 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

67%67% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

41%41% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

40%40% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

36%36% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

11%11% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

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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