Airy – a smart journal to write photo-rich entries and analysis for me

Hacker News

Hi HN, I'm Steven. As a 4 year journal writer myself, current journal apps are so time-consuming and tedious that it becomes a chore rather than an enjoyment. But I believe most of us want to build a habit of journaling. So I built Airy, an app that does it for me. (Airy = AI diaRY, lol) Airy is a smart journal that automatically creates photo-rich journal entries and analysis. Simply talk about your day, or don't, and Airy will automatically create a beautiful journal entry that summarizes everything, including relevant photos, activities, and memories. You can also retrieve any of your past memories or thoughts with a simple question. Key Features: -Record: Never forget a memory again. Record any memory instantly with voice, text, or camera. -Review: Review day, or even year, with one click. All your memory, photos, and activities will be summarized for you. -Retrieve: From favorite playlists to summaries or your recent inspirations, retrieve any memory with a simple question. I would love to hear your feedback and thoughts on how we can improve Airy. We are in the beta launch phase, and your input is invaluable to us. Thank you for checking out Airy!

Visit product View on Hacker NewsMay 30, 2024

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

82%82% 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.

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

71%71% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

46%46% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

41%41% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

34%34% 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

25%25% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: smart · Missing: web3, chat, crypto

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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