Inspiration
Creators, marketers, and podcasters spend hours manually clipping and repurposing content. We wanted a tool that could make this instant - turning long-form videos into viral, multilingual, and reusable assets powered by AI.
What it does
Korai transforms long-form content into post-ready viral clips with multilingual audio and captions, auto reframing, and multi–aspect ratio exports for all platforms. It also enables chat with video content, letting users extract insights to create blog posts, viral threads, newsletters, and client follow-ups - making it valuable across marketing, sales, and podcast studios.
How we built it
We built it by mainly working on video processing pipelines 🔗 Detailed developer docs: https://docs.korai.run/ 📺 Architecture overview at the end of demo: YouTube Demo
Challenges we ran into
Implementing AI auto reframing was tough — we finally solved it using LR-ASD model. Synchronizing speaker audio with multilingual captions and handling MCP authentication and security for the agentic chat were also major hurdles.
Accomplishments that we're proud of
Successfully generating multilingual audio and captions for viral shorts required heavy GPU-based processing and seamless synchronization — achieving this end-to-end automation was a huge milestone.
What we learned
We gained deep insights into video processing system design, FFmpeg orchestration, and multimodal pipeline optimization — building scalable, efficient, and developer-friendly AI workflows.
What’s next for Korai
We’re expanding into Agentic MCP Chat with 500+ app integrations for automated workflows. Example: a travel agency or food vlogger could summarize videos from a Google Sheet → extract locations → auto-generate itineraries → and save everything to Notion. We also plan to add clip search and explore visual–language model research. If we win this hackathon, the prize will be used as a grant to scale Korai’s infrastructure and research efforts.
Built With
- amazon-web-services
- cerebras
- fastapi
- ffmpeg
- gcp
- huggingface
- inngest
- neondb
- nextjs
- prisma
- redis
- tensorflow
- typescript
- vercelaisdk
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