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Long videos in, on-brand Shorts and Reels out. A content repurposing studio with brand memory, built at the Product Space × Wispr Flow AI Hackathon 2026.
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查看完整 README ↗Brands and creators sit on hours of podcasts, workshops and founder talks. Turning them into Shorts and Reels is slow, and generic AI clippers forget your voice, so every caption needs the same fixes again: too salesy, too many emojis, wrong language.
ClipwellAI keeps a style card for each brand that learns from your edits and from how your posts actually performed. The tenth clip needs fewer fixes than the first.
Built on 31 October 2026 for Problem Statement 01, Content Repurposing Studio with Brand Memory, at the Product Space × Wispr Flow AI Hackathon, by voice with Wispr Flow.
| Step | What happens |
|---|---|
| 1. Long video in | Upload a video (up to 4 hours) or paste a YouTube link. The audio is pulled out in the browser and transcribed with word-level timings. English, Hindi, Hinglish or auto-detect. |
| 2. Brief → clip picks | Say what you want, typed or spoken with Wispr Flow. The AI returns 3 to 5 clips, each with a hook, a score out of 100 and a plain-language reason for the pick. |
| 3. Edit and export | Trim each clip, choose framing (centre, left, right, or split for two speakers) and export a 9:16 MP4 with word-by-word captions burned in. Rendering happens in the browser. |
| 4. Copy per platform | An Instagram Reels caption and a YouTube Shorts title and description, with hashtags, in the brand's tone and language. |
| 5. Brand memory | Change the copy in plain words: "too salesy, drop the emojis, max two hashtags". Tick Make this a rule and the style card learns it, so every future clip follows it. |
| 6. Content calendar | Plan the next 7 days of posts from your clips and export the plan as a CSV for Google Sheets. |
| 7. Learns from results | After posting, mark each clip Great, OK or Poor. What worked and what flopped goes back into the style card and shapes the next picks. |
| Layer | Choice |
|---|---|
| App | Next.js 15 (App Router, TypeScript, Tailwind CSS v4) on Vercel |
| Auth and data | Supabase: Google sign-in, Postgres with row-level security |
| Clip picks, copy, style-card learning | Anthropic Claude, with structured (tool-use) output |
| Transcription | Groq Whisper large-v3-turbo, audio sent in 5-minute parts |
| Video | ffmpeg.wasm in the browser: audio extraction, 9:16 framing, burned-in captions |
app/ pages and API routes (clips, copy, edit, style card, transcribe, youtube)
components/ studio UI: upload, clip picks, editor, copy panel, style cards, calendar
lib/ Claude client, prompts, storage, media (ffmpeg) helpers
supabase/ database schema and row-level security policies
git clone https://github.com/RounakBisht/ClipwellAI.git
cd ClipwellAI
npm install
cp .env.example .env.local # fill in your own keys
npm run dev
You need a Supabase project (run supabase/schema.sql, turn on Google sign-in), a Groq API key and an Anthropic API key. The full checklist, including deploying to Vercel, is in docs/SETUP.md. To try it without Supabase, set NEXT_PUBLIC_DEMO_MODE=true and your data stays in the browser.
Rounak Bisht
Kartik Manral
Built with Claude Code as our coding partner; it is credited as co-author on the commits.
MIT: free to use, change and share.