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RemindEat - never forget what you ate

Hacker News

RemindEat - never forget what you ate

I like going out with my fiancé and tasting new dishes in new places. Once I get to a place I've been before I never remember what I previously ate. So we decided to sit down and think of something we could do to help solve this and came up with our first project together. RemindEat emails and/or sends you an SMS when you check-in at any food place, reminding you to note down what you ate. Next time you check-in you'll be reminded of what you've eaten there before and to note down what you'll eat this time. Its built on top of Flask, Twitter Bootstrap, uses Twilio for SMS, and Postmark for emails. Obviously powered by Foursquare. Please go to http://remindeat.com, try it out and let me know what you think.

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Actual performance

5points
4comments
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
63%63% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
60%60% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntOn track for Day 1 leaderboard · Strong signals: new, email · Missing: mac, agents, macos
58%58% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · 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 · Missing: mobile apps, ios, personal
30%30% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
13%13% 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.

Incorrect prediction on native model

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