Replay – A private, on-device Google Timeline replacement for iOS

Hacker News

I got fed up with Google Timeline's awful location tracking and control, so I built my own. Replay's a native app built entirely on Swift. It runs in the background, automatically saves your visits and routes, detects activity type (walk/cycle/drive/transit), and stores everything locally on your device. No account. No subscription. No server ever touches your data. One-time purchase. A few technical decisions I made that are worth calling out: - All processing happens on-device using CoreLocation and CoreMotion - No backend, which means no breach surface for your location data - Battery impact is minimal — same approach as iOS's own significant-location-change API, with minimal active location tracking to produce clean polylines - We use SwiftUI for most of the regular layout, but UIKit for the map & bottom sheet for fine control What I mainly use it for is to know where I've been on my holidays, but it's also cool to see insights on my daily patterns so I just leave it on! Check out the screenshots on the AppStore! https://replayapp.jaxtam.dev Hope Replay would be useful for you. I'm open to any feedback. Thanks everyone!

Visit product View on Hacker NewsMar 27, 2026

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

85%85% 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

78%78% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

51%51% 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: ios, apps, google · Missing: mobile apps, personal, entrepreneurs

49%49% 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

28%28% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: subscription, active · Missing: arr, mrr, revenue

23%23% 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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