A private automatic travel tracker and life journal for iOS

Hacker News

Hi HN, I made Acti, an iOS app that automatically records the places you visit and builds a timeline of your life. It’s totally private, no accounts, no cloud, everything stays local on your device. The motivation: I wanted something like Google Maps Timeline, but without data collection or ads. Acti just runs in the background, asks you to name new places once, and then remembers them forever. You can also add photos, comments, and ratings. What I’m struggling with: because there are no registrations, I don’t really know how to connect with users, gather feedback, or even measure if people keep using it. I’d love feedback on both: a) the product itself (is this useful to you?), b) and ideas for how to stay connected with users in a privacy-respecting way. Thanks for reading!

Visit product View on Hacker NewsAug 20, 2025

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Launch Intel predictions

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

84%84% 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: ios · Missing: supports, reddit linkedin, podcasting

80%80% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Strong signals: ios, google, users · Missing: mobile apps, personal, entrepreneurs

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

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

41%41% predicted probability of success on AppSumo, 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.

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

20%20% 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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