Fashion Discovery Platform

India's fashion discovery engine for Instagram-native D2C brands

A production-ready platform that aggregates 250+ digital-first fashion brands, enables advanced filtering, and redirects traffic to original brand websites.

🚫 NOT a marketplace - Discovery + Filtering + Redirection only

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Features

Core Platform

• ✅ Advanced Filtering - Filter by category, price band, aesthetic, fit, fabric, and more
• ✅ Smart Ranking - Algorithm-based brand scoring using signals (IG native, Meta ads, drops, etc.)
• ✅ Redirect Tracking - Analytics on clicks, referrers, and UTM parameters
• ✅ Responsive Design - Beautiful, modern UI built with Next.js and Tailwind CSS

Discovery Automation

• 🤖 Meta Ads Discovery - Find brands advertising on Meta platforms
• 🛍️ Shopify Detection - Identify D2C Shopify stores
• 📱 Instagram Integration - Discover Instagram-native brands
• 🏪 Marketplace Mining - Extract brands from Furrl, LBB, Shiprocket Discover
• ⚡ Auto-Approval - Brands with score ≥7 auto-approved weekly

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Tech Stack

• Frontend: Next.js 14 (App Router), React, TypeScript, Tailwind CSS
• Backend: Next.js API Routes
• Database: PostgreSQL 15 (via Homebrew)
• Icons: Lucide React
• Deployment: Vercel (recommended)

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Quick Start

1. Install PostgreSQL

brew install postgresql@15
brew services start postgresql@15

2. Create Database

/opt/homebrew/opt/postgresql@15/bin/createdb fashion_discovery

3. Clone & Install

cd /path/to/clothing
npm install

4. Environment Variables

Create .env.local (optional - defaults work for local PostgreSQL):

DB_HOST=localhost
DB_PORT=5432
DB_NAME=fashion_discovery
DB_USER=  # Leave empty to use current user
DB_PASSWORD=

5. Run Database Migrations

/opt/homebrew/opt/postgresql@15/bin/psql -d fashion_discovery -f supabase/migrations/001_initial_schema.sql
/opt/homebrew/opt/postgresql@15/bin/psql -d fashion_discovery -f supabase/migrations/002_seed_data.sql
/opt/homebrew/opt/postgresql@15/bin/psql -d fashion_discovery -f supabase/migrations/003_increment_function.sql

6. Seed Sample Brands

npm run db:seed

This will add 10 sample brands with tags.

7. Start Development Server

npm run dev

Open http://localhost:3000

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Project Structure

clothing/
├── src/
│   ├── app/
│   │   ├── api/
│   │   │   ├── brands/route.ts       # Brand search & filter API
│   │   │   └── r/[slug]/route.ts     # Redirect tracking API
│   │   ├── page.tsx                  # Main page
│   │   └── layout.tsx
│   ├── components/
│   │   ├── BrandCard.tsx             # Brand display card
│   │   └── FilterPanel.tsx           # Filter sidebar
│   ├── lib/
│   │   ├── db.ts                     # PostgreSQL client
│   │   └── utils.ts                  # Ranking & utilities
│   └── types/
│       └── database.ts               # TypeScript types
├── scripts/
│   ├── seed-brands.ts                # Brand seeding script
│   └── weekly-discovery.ts           # Discovery automation
├── supabase/
│   └── migrations/                   # Database migrations
└── package.json

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Database Schema

Tables

• brands - Main brand data with signals and metadata
• categories - Brand categories (Streetwear, Formals, etc.)
• tags - Filterable tags (fit, aesthetic, fabric, etc.)
• brand_tags - Many-to-many relationship
• redirects - Click tracking and analytics
• discovery_queue - Automated brand discovery queue

Key Indexes

• Category, price band, slug, active status
• Tag categories and applicability
• Redirect timestamps for analytics

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API Endpoints

GET /api/brands

Search and filter brands.

Query Parameters:

• category - Comma-separated category slugs
• price - Comma-separated price bands (₹, ₹₹, ₹₹₹, ₹₹₹₹)
• tags - Comma-separated tag slugs
• search - Brand name search
• sort - relevance | popular | new
• limit - Results per page (default: 50)
• offset - Pagination offset

Response:

{
  "brands": [...],
  "total": 250,
  "filters": {
    "categories": [...],
    "priceBands": [...],
    "availableTags": [...]
  }
}

GET /api/r/[slug]

Redirect to brand website with tracking.

Query Parameters (optional):

• utm_source, utm_medium, utm_campaign

Response: 302 redirect to brand website

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Brand Discovery System

Running Discovery

npm run discovery:run

This will:

1. Search Meta Ads Library for fashion brands
2. Crawl Shopify stores
3. Mine marketplaces (Furrl, LBB, etc.)
4. Score and add brands to discovery queue
5. Auto-approve brands with score ≥7

Discovery Scoring

Signal	Points
Meta Ads Active	+3
Shopify-backed	+2
Limited Drop Language	+2
Instagram Native	+2
No Offline Stores	+1

Auto-approval threshold: 7+ points

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NPM Scripts

# Development
npm run dev              # Start dev server (port 3000)

# Database
npm run db:seed          # Seed sample brands

# Discovery
npm run discovery:run    # Run brand discovery

# Production
npm run build            # Build for production
npm start                # Start production server

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PostgreSQL Management

Start/Stop PostgreSQL

# Start
brew services start postgresql@15

# Stop
brew services stop postgresql@15

# Restart
brew services restart postgresql@15

Connect to Database

/opt/homebrew/opt/postgresql@15/bin/psql -d fashion_discovery

Useful SQL Queries

-- Count brands
SELECT COUNT(*) FROM brands;

-- View all categories
SELECT * FROM categories ORDER BY display_order;

-- Top brands by clicks
SELECT name, total_clicks FROM brands ORDER BY total_clicks DESC LIMIT 10;

-- Discovery queue status
SELECT status, COUNT(*) FROM discovery_queue GROUP BY status;

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Deployment

Vercel with Remote PostgreSQL

1. Set up a PostgreSQL database (Railway, Supabase, Neon, etc.)
2. Push to GitHub
3. Import project in Vercel
4. Add environment variables:
   • DB_HOST
   • DB_PORT
   • DB_NAME
   • DB_USER
   • DB_PASSWORD
5. Run migrations on remote database
6. Deploy

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Scaling to 2,500+ Brands

The system is designed to scale:

1. Database Indexes - Optimized for fast filtering
2. Connection Pooling - 20 max connections
3. Pagination - Built-in limit/offset
4. Discovery Automation - Weekly brand ingestion
5. CDN - Vercel Edge for static assets

Performance Targets

• Search/filter queries: <200ms
• Redirect tracking: <100ms
• Discovery run: <5 minutes

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Troubleshooting

PostgreSQL Not Starting

brew services restart postgresql@15

Database Connection Errors

Check if PostgreSQL is running:

brew services list | grep postgresql

Reset Database

/opt/homebrew/opt/postgresql@15/bin/dropdb fashion_discovery
/opt/homebrew/opt/postgresql@15/bin/createdb fashion_discovery
# Then re-run migrations

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Contributing

Adding Brands Manually

1. Add brand data to scripts/seed-brands.ts
2. Run npm run db:seed

Adding New Tags

1. Add to supabase/migrations/002_seed_data.sql
2. Re-run migration
3. Update FilterPanel.tsx if needed

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License

MIT

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Support

For issues or questions, open a GitHub issue.

Built with ❤️ for India's fashion ecosystem