Albums Backup – USB tool to back up iPhone photos

Hacker News

Hey HN, I built a tiny offline tool to help back up iPhone/iPad photos and videos to PC or Mac via USB. No iCloud, no accounts, no cloud storage — just straight device-to-device transfer. Originally made it for someone close to me who had tens of thousands of photos but didn't want to deal with subscriptions or cloud storage. Thought it might be useful for others too, so putting it out there. It keeps Live Photos, 4K videos, RAW files, and transfers quickly without compression. Works on both Windows and macOS. Site (simple landing page): https://albumsbackup.framer.website/ Would love any feedback, ideas, or just to know if anyone else needed something like this.

Visit product View on Hacker NewsApr 28, 2025

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

88%88% 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: mac, macos, tiny · Missing: agents, agent, cursor

81%81% 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

53%53% 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

47%47% 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: video · Missing: mobile apps, ios, personal

35%35% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

13%13% 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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