I built LoveMemo to surprise my wife

Hacker News

I wanted to find a different way to show my wife that I love her, so I made LoveMemo. Quick texts and typical presents were not my thing. I wanted something more an experience that was loving, personalized, and never forgotten. LoveMemo is the result. The app guides you through making a unique web page that includes: - Names of the couple - A counter displaying how long they have been together - An amazing photo slideshow - Some background music for the atmosphere - A personal love message When the work is complete, LoveMemo makes a nice card with a QR code that connects to the page. You can give the card to your partner and let the surprise work its magic. In fact, every memo results in a quickly loading public page that is created for easy sharing, while the mobile app is all about helping the user to create in a simple and emotionally engaging way. This idea was just my personal project, but I thought maybe other people would like it too. Your feedback would be great! Thanks for your time.

Visit product View on Hacker NewsDec 29, 2025

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

95%95% 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: user, code · Missing: mac, agents, macos

73%73% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive

54%54% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

46%46% predicted probability of success on TrustMRR, 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

39%39% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

14%14% 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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