Developers Build AI Virtual Try-On App StyleSense Using Aurora and Vercel in 72 Hours

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A development team built StyleSense, an AI-powered virtual try-on application, during a 72-hour hackathon to address the problem of online clothing returns, which cost the retail industry over $816 billion annually. The app allows users to upload a selfie and preview clothing items from any product URL on their own image using AI models from Runway ML and Anthropic Claude. The backend runs on FastAPI with Amazon Aurora PostgreSQL Serverless v2 as the primary database, chosen for its ability to scale to zero during idle periods and support IAM-based authentication that eliminates the need to store database passwords in code. The Next.js frontend was deployed on Vercel, with both the frontend and database hosted in the Mumbai region to keep database round-trip latency under 20 milliseconds. Supabase was used separately to handle authentication, real-time features, and social functionality, while Aurora managed core transactional data requiring SQL joins.

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