Built an AI bot to be my be personal trainer and nutritionist

Hacker News

I built an AI-powered fitness bot that sends personalized workout and nutrition tips straight to your Telegram. You can send photos of your meals for calorie/macros, or ask anything else about fitness or nutrition, it’s really simple. Plus, the bot checks in with you to keep you on track. Honestly, I got tired of feeding GPT-4 the context of my profile every time I wanted some simple nutrition answers. I’m also a total gym rat, always helping friends with fitness questions. So I made this both for myself and other people too. If you need quick feedback on meals or a fitness mentor, give it a try. Would love to hear what you think! Any feedback would be greatly appreciated :)

Visit product View on Hacker NewsNov 21, 2024

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

76%76% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

TrustMRRFits verified-revenue profile · Strong signals: personal, answers, way · Missing: mobile apps, ios, entrepreneurs

63%63% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

50%50% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: mac, context · Missing: agents, macos, agent

34%34% predicted probability of success on Product Hunt, 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

18%18% 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 · Missing: arr, mrr, revenue

17%17% 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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