Reflectr, an AI Notebook on iOS and Android

Hacker News

I created Reflectr as a space to freely and privately post your thoughts, ideas, observations, and mental notes without the pressure of social media or sharing, just for yourself. I wanted to leverage the recent breakthroughs in generative AI and incorporate those capabilities into Reflectr to help generate automated feedback and insights from your posts, such as comments, mood indicators, tags, emojis, daily recaps, and writing tips to help you reflect and be more focused and productive. I have an exciting roadmap planned with more features and AI-generated insights to help you focus on what brings you joy and boosts your productivity. It's now available on both the iOS and Android App Stores, links below: iOS: https://apps.apple.com/us/app/reflectr/id6446969075 Android: https://play.google.com/store/apps/details?id=net.dailylabs.... I'd love for you to try Reflectr and share your honest feedback! If you have any questions or suggestions, I'm here to answer them! Thank you, Sashi.

Visit product View on Hacker NewsApr 27, 2023

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Actual performance

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Did not reach leaderboard

Launch Intel predictions

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

92%92% 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: ios, apps, google · Missing: mobile apps, personal, entrepreneurs

69%69% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Product HuntOn track for Day 1 leaderboard · Strong signals: apple, google, apps · Missing: mac, agents, macos

66%66% 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

36%36% 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

28%28% predicted probability of success on Acquire.com, 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

23%23% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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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