FileLever – Local-first folder sync with preview-before-write

Hacker News

Hi HN — Checkout FileLever, to sync or backup your photos, videos and more. I built FileLever as a preview-first tool to review all the changes before a sync or backup runs. FileLever works with local drives, external HDD, NAS, USB drives, SD cards, Dropbox, locally synced Google Drive. Filelever started as a folder comparison/sync tool, but I have recently added Apple Photos archival workflow to the growing list. Take a look and let me know if you would like to see something more in this tool, especially from anyone here who manages large photo libraries, external drives, or backup folders.

Visit product View on Hacker NewsSep 15, 2026

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Launch Intel predictions

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

79%79% 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: started · Missing: supports, reddit linkedin, podcasting

61%61% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

55%55% 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

39%39% 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 · Missing: https docs, excited, just released

34%34% 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

16%16% 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

3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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