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Snap a Pic of Your Fridge, Let AI Dish Out Ingredients and Recipes

Hacker News

Snap a Pic of Your Fridge, Let AI Dish Out Ingredients and Recipes

Introducing my latest weekend/evening project: Fridge Leftovers AI Ever found yourself staring at the contents of your fridge, wondering what to cook with the leftovers? The app simplifies meal planning by analyzing photos of your fridge contents and suggesting delicious recipes! I'd love to hear your thoughts and feedback on the app! Your input helps me make Fridge Leftovers AI even better. Feel free to drop your comments below or shoot me a message. Cheers!

Visit product View on Hacker NewsMar 8, 2024

Actual performance

3points

Did not reach leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos

66%66% 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.

TrustMRRLess likely to generate early MRR · 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

38%38% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

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

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

26%26% 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

19%19% 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

5%5% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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