The original title is: "How We Built StyleSense: AI Virtual Try-On Powered by Amazon Aurora & Vercel"

Short summary

StyleSense solves $816B annual returns problem by letting shoppers see clothes on their body before buying using AI try-on powered by Claude vision and Runway ML. This technical deep-dive explains their 72-hour hackathon build using Aurora PostgreSQL Serverless, Vercel, and IAM-authenticated connections with zero credentials in code. Key learning: serverless Aurora scales to zero cost, token-based auth requires careful refresh timing in connection pools, and third-party ML APIs need public HTTPS URLs.

• •Virtual try-on product using Claude vision + Runway ML, built in 72 hours for hackathon competition
• •Aurora PostgreSQL Serverless v2 with IAM token auth eliminates password storage; scales to zero between demos
• •Token refresh in SQLAlchemy connection pool is critical (15-min expiry); all image URLs must be public HTTPS for Runway API

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