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VidSbo – AI Storyboard Generator from Videos and Ideas

Hacker News

VidSbo – AI Storyboard Generator from Videos and Ideas

I built VidSbo ( https://vidsbo.com ) to solve a specific pain point in video production: manually breaking down references is tedious. The tool does two main things: Video to Prompt: It analyzes camera angles, lighting, and pacing of existing videos (e.g., TikToks/Shorts) and reverse-engineers them into a shot list/script. Idea to Storyboard: Converts text into visual boards for pitching. It exports to JSON, which I found useful for feeding into AI video models like Sora or Veo to get more consistent results.

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
74%74% 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.
AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive
59%59% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Product HuntOn track for Day 1 leaderboard · Strong signals: model, models, visual · Missing: mac, agents, macos
59%59% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: video · Missing: mobile apps, ios, personal
55%55% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: exist, existing, 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
28%28% 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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