AI

AI Powered Grocery List Suggestor

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AI Powered Grocery List Suggestor

Hey HN, I just build this app and published it. It's my first swift app that I published on app store. I am open to feedback and suggestions. You do not need to sign up or pay anything to try, although you would need to download it. Here is what it does: - Given your dietary restrictions that you choose from the profile page it suggests you grocery lists. -If you want to cook a dish maybe something spesific and you are doing grocery shopping but do not know what to buy then this app helps you if you type in the food name you want to cook and it generates a grocery list. -The last feature is that it can suggest random meals to you from like 800 cuisines. For this part, I opened wikipedia and searched for all the different cuisines in the world after literally copy pasting 800 cuisine names in a list and by randomly selecting one of the cuisines, the app then makes an api request to openai to come up with a dish within that cuisine and to create a grocery list for that spesific dish. It was a side project for me but I wanted to see how far can I push this but I stopped after a while and I did not add any more features. Would love to hear your thoughts and any feedback you have :) Cheers!

Visit product View on Hacker NewsFeb 15, 2025

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

86%86% 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.

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

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

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

42%42% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

30%30% 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 · Missing: plus, platform, intuitive

28%28% 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

15%15% 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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