Courtney – Transform Articles into TikTok-Style Videos Instantly

Hacker News

Meet Courtney, an AI tool that transforms any article into a TikTok-style video in minutes. Just paste a URL, and Courtney handles the rest: 1. Script Writing 2. Voiceover Generation 3. Visual Demo Recording 4. Subtitle Addition 5. Seamless Syncing Built With Frontend: Next.js + NextUI Backend: Supabase AI & Video: Fal AI, Puppeteer, ElevenLabs, FFmpeg More coming soon! DM me @lucasmandelbaum on X with feedback :)

Visit product View on Hacker NewsJan 15, 2025

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: visual, elevenlabs · 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.

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

55%55% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: video · Missing: mobile apps, ios, personal

45%45% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

32%32% predicted probability of success on Indie Hackers, 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.

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

21%21% 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

13%13% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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