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Caloree for iOS First Beta

Hacker News

Caloree for iOS First Beta

Hi all , around a year ago after becoming frustrated with existing calorie counter/diet tracking apps mostly due to the fact that you have to pay a monthly subscription fee. It seems like these days everything is subscription-based. Another annoyance was that some apps didn't respect my privacy and/or forced me into becoming a part of their own social network. Hence, today I am happy to announce that I am releasing a first, early beta version of Caloree. What is Caloree? Caloree is a simple calorie tracker that respects your privacy and does not try to sell you a subscription. Instead, once we launch Caloree, we will offer 2 tiers of one-time in-app purchases: * Pro: you will get access to hundreds of thousands of products, be able to scan the barcodes of these products * Ultra: you gain the ability to plan several days in advance and in the future you will get nifty features, such as image recognition, Apple Watch support, Widgets, etc. What to expect of the beta? As mentioned, this is an early build, so there will be rough spots here and there. I am also working on additional features as I am writing this. The product catalog is still quite raw, currently lacking basic foods such as eggs and milk, which will follow in later beta versions. The weight screen still needs some love and also data entry could be better. Participating If you would like to try out Caloree on your iPhone or know some friends who would like to try it out, feel free to install it: https://testflight.apple.com/join/65dEEqFM. I'll be scanning this post for any comments or feedback that you might give. If you would like to participate more actively you can also join my Discord server (https://discord.gg/h4XCmkPq) where I'll try to be available at least once a day to discuss feature requests, learn about any issues that you found or anything else that could be useful regarding Caloree. I hope you like this early release of Caloree. Happy testing! Rudy

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Actual performance

2points
Did not reach leaderboard

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Indie HackersFits the IH revenue-focused audience · Strong signals: ios · Missing: supports, reddit linkedin, podcasting
91%91% 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: apple, apps, code · Missing: mac, agents, macos
61%61% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: ios, apps, month · Missing: mobile apps, personal, entrepreneurs
61%61% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: exist, existing, io · Missing: https docs, excited, just released
42%42% 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
38%38% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: subscription, active · 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.

Correct prediction on native model

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