Editly

Inspiration 💡

Online personal branding is a daunting science for many beginner content creators. Thankfully, existing media trends tell us how to make simple videos go viral.

What it does 🧑‍💻

The user simply uploads a raw video and selects existing videos as inspiration. Then the app outputs an AI-edited video infused with viral video formats.

How we built it 🛠️

Front: NextJS, TailwindCSS Back: AWS Lambda, Docker Dev: Vercel

Challenges we ran into ⚠️

• Fetching video data (title, caption, video, etc.) from Instagram Business API
• Operating AWS Lambda functions across several local machines
• Integrating multiple ML model layers for video processing (Hugging Face, OpenAI Whisper)

Accomplishments that we're proud of 🏆

• Learning and integrating an extremely complex tech stack in 24 hours
• Extracting sound/visual effects from Instagram videos
• Implementing AI video editing with raw user clips

What we learned 📚

Our biggest lesson was choosing too many open ended and ambitious MVP features. We should've relied way less on AI processing.

What's next for Editly 💭

We want to provide a wider range of editing options for video format infusion. This can include plot points, color effects, and more.

We also want to allow users to share inspiration boards via a community tab. Users would be able to create boards that contain video and/or creators that inspired individual video edits.

Built With

• amazon-web-services
• flask
• lambda
• nextjs
• python