How We Built StyleSense: AI Virtual Try-On Powered by Amazon Aurora & Vercel

Online clothing returns cost the industry over $816 billion a year. The root cause is simple: shoppers can't see how clothes look on their body before buying. We built StyleSense to fix that — an AI-powered virtual wardrobe where you upload a selfie, add clothes from any product URL, and instantly see yourself wearing them.

Here's how we built it, and why Amazon Aurora PostgreSQL and Vercel were the right choices for a 72-hour hackathon build.

We needed a database that could handle:

Aurora Serverless v2 solved all three. It scales to zero between test runs, scales up instantly under load, and supports IAM authentication — meaning our FastAPI backend never stores a database password.

Instead of a static DATABASE_URL

with a password, we use boto3 to mint a short-lived token at connection time:

import boto3

def get_iam_token():
    client = boto3.client("rds", region_name="ap-south-1")
    return client.generate_db_auth_token(
        DBHostname="stylesense.cluster-c9cswq8kqykn.ap-south-1.rds.amazonaws.com",
        Port=5432,
        DBUsername="stylesense_app",
        Region="ap-south-1",
    )

We wire this into SQLAlchemy's connection pool via a custom creator

function that refreshes the token before each new connection — tokens expire in 15 minutes, so this is essential:

from sqlalchemy import create_engine

engine = create_engine(
    "postgresql+psycopg2://",
    creator=lambda: psycopg2.connect(
        host=AURORA_HOST,
        port=5432,
        dbname="stylesense",
        user="stylesense_app",
        password=get_iam_token(),
        sslmode="require",
    )
)

No password in .env

. No password in CI. No password in the repo. Just an IAM role.

We kept it lean — 4 core tables in Aurora:

Auth and social (friendships, chat threads) stay in Supabase, which already has Row-Level Security and Realtime built in. Aurora handles the data that benefits from SQL joins and full ACID transactions — like "show me all try-ons for items in category X that this user saved as outfits."

Our Next.js frontend deploys to Vercel with three environment variables and zero configuration files. The things that made the biggest difference:

Edge middleware for auth: Supabase session refresh runs at the edge on every request, so protected pages never flash unauthenticated content. This is one middleware.ts

file:

// middleware.ts
import { createServerClient } from "@supabase/ssr";
import { NextResponse } from "next/server";

export async function middleware(request: NextRequest) {
  // Refreshes the Supabase session cookie on every request
  // Redirects to /login if the user is not authenticated
}

Mumbai region: We deployed both the Vercel frontend (bom1

) and Aurora (ap-south-1

) in Mumbai, keeping API latency under 20ms for the database round-trip.

The one gotcha: Runway ML requires all image URLs to be public HTTPS. Localhost URLs fail silently. Every selfie and wardrobe image gets re-hosted to Supabase Storage before being passed to any Runway API call — Vercel's environment variables made switching between dev and prod URLs painless.

The "wow moment" flow that we demoed:

The entire pipeline is async. FastAPI fires each Runway task and returns a task ID; the frontend polls via Zustand store state that survives page navigation.

Aurora IAM token refresh in connection pools: SQLAlchemy's connection pool reuses connections, so a token minted at startup expires mid-session. The fix: use NullPool

or override the creator

so a fresh token is minted for every logical connection. We went with the creator

approach and a short pool recycle time.

Runway image URL requirement: Every image URL sent to Runway must be a public HTTPS URL. During development this means all local uploads get re-hosted to Supabase Storage before the Runway call — an extra round-trip but essential.

Credit budget discipline: Runway gen4.5 video costs 60-100 credits per 5 seconds. With a 50,000-credit budget, we used gen4_image_turbo (2 credits) for all dev testing and reserved the full quality models for demo recordings.

The full source is on GitHub. The live demo runs on Vercel at [https://style-sense-steel.vercel.app/].

Built in 72 hours for the H0: Hack the Zero Stack with Vercel v0 and AWS Databases hackathon.

#H0Hackathon