What Happens to Your Secrets When You're Gone? Inspired by Real Events

Hacker News

Hey everyone! I recently launched a project that was inspired by something I read in the news — a Japan Airlines flight dropped 26,000 feet in 10 minutes, and passengers began writing final messages and wills midair. That story stayed with me. It made me think about how unpredictable life is... and how many of us have things we want to pass on only after we're gone. Not just the serious stuff like wills or passwords, but maybe a secret diary, a note of love, or simply instructions we never got to share. That’s why I built FinalNotify [com] – a tool that lets you securely store important info, secrets, and messages, and have them delivered to your trusted contact only when something happens to you. It’s like a digital time capsule with purpose and privacy. It’s a deeply personal project, and I’d love your feedback or support I’d love to hear your feedback—what works, what doesn’t, and what could be improved! You can try it out here: https://www.finalnotify.com

Visit product View on Hacker NewsJul 25, 2025

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

87%87% 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.

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

59%59% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: 000, io · Missing: https docs, excited, just released

50%50% 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 · Missing: mac, agents, macos

50%50% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

33%33% 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

11%11% 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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