Widget Cast – Video Widgets for Your iPhone and Apple Watch

Hacker News

Hello! I've just released Widget Cast today, it's a little app to make looping animated widgets for iOS. Take any video and and you can trim to 10 seconds or less, then apply a load of effects like CRT, night vision, thermal, colour tint, etc - then see it animate away on your home screen. App store: https://apps.apple.com/gb/app/widget-cast-video-widgets/id67... Got a glowing futuristic website here too: https://widgetcastapp.com If you have an Apple watch, you can view them there too. Could be a special moment or person, or just a dinosaur jumping up & down (which is also special). It's free with some effects behind IAP (there are sort-of pay-what-you-want tiers). No subscriptions or ads. Hopefully it's good fun!

Visit product View on Hacker NewsMay 20, 2026

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

86%86% 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 · Missing: mac, agents, macos

75%75% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

67%67% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: just released, ide, io · Missing: https docs, excited, exist

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.

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

31%31% 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 · Missing: arr, mrr, revenue

19%19% 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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