Capit – Social Media Image Caption Generator

Hacker News

Hey HN! I just recently released my latest iOS App, Capit - it is a simple app built to generate captions for social media posts, all directly from images & video, utilizing gpt-4-vision. Users just choose an image, select a tone, and get 5 great caption options. My latest update adds Profiles to allow you to save your settings for different social media profiles, along with a simple caption editor to let you customize your captions further. The app is a subscription service - but lets you try it for free if you just hit the X button on the paywall. I built the app as my wife runs a small business for which Instagram is a huge traffic generator...but she often gets stumped at what to write in terms of captions, especially when we've been open for years and it feels like you are just recycling content in many cases. Capit isn't really meant to automatically post for you - it is a tool for improving your own creativity. I'd appreciate any & all feedback!

Visit product View on Hacker NewsDec 23, 2023

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

93%93% 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: user, open · Missing: mac, agents, macos

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

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

66%66% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Strong signals: users · Missing: plus, platform, intuitive

57%57% 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

36%36% 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 · Strong signals: subscription · Missing: arr, mrr, revenue

29%29% 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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