WorkSplit – iPhone camera that keeps work photos separate

Hacker News

I built WorkSplit, a tiny iPhone app to keep work photos separate from personal ones, stored locally on device. Problem As a field technician I often mixed project photos with my private camera roll. That made documentation messy and raised privacy issues when sharing or backing up. What it does - Separate, work-only camera inside the app (shoot directly into a selected project/album) - Optional import from the system Photos app into a project - Fast retrieval of unsorted shots and quick assignment to a project - Local-only storage on the iPhone (no accounts, no cloud) Who it’s for Tradespeople, technicians, and freelancers who document jobs and want clean separation and privacy. Link (App Store): https://apps.apple.com/ch/app/id6753669162 I’d love feedback on: - Does the capture→project flow feel right, or what’s missing for field work? - Must-have features you’d expect (bulk actions, export flows, metadata)? - Any iOS edge cases I should account for? Happy to answer technical or product questions. – Adrian

Visit product View on Hacker NewsOct 29, 2025

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

82%82% 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: apple, apps, tiny · Missing: mac, agents, macos

81%81% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

52%52% predicted probability of success on TrustMRR, 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

32%32% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

30%30% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

18%18% 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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