PassPad

Full-stack Re-Commerce platform for video games

AI-powered product recognition • Headless Shopify • Production-ready

Visit PassPad

About the project

PassPad is a re-commerce startup I founded with my cousin to digitize the used video game market. Our platform solves a classic market problem: the high manual effort required to value collections.

As a full-stack developer and analyst, my goal was to consistently replace manual processes with technology. We built a highly automated pipeline that dramatically reduces admin work using computer vision and smart pricing algorithms. Today the system manages over 10,000 items largely autonomously—tasks that used to take hours now run in the background.

The vision

PassPad unites two worlds in one modern platform:

Buyback

Users sell used games and consoles—with an AI scanner for fast recognition and a transparent checkout flow.

Shop

Used products are sold through a headless Shopify shop—SSR, SEO-optimized, and scalable.

Technology stack

Next.js 16

App Router

React 19

Server Components

TypeScript

End-to-end types

PostgreSQL

Prisma ORM

Shopify

Storefront API

Gemini

AI integration

PostHog

Analytics

Google Tag Manager + Analytics

Tracking & analytics

Feature spotlight

AI scanner

The signature feature: less typing, faster offers, better conversion.

  • ✓ Multi-image upload with progress states
  • ✓ Batch-based async processing
  • ✓ Admin mode & A/B testing controls
  • ✓ Server-side asset handling (S3)
AI-Powered

Headless shop

Shopify Storefront API with typed GraphQL queries, SSR, and SEO foundations.

In our shop we sell processed video games and consoles.

Admin pipeline

Dedicated admin tooling for managing purchases, products, coupons, and more.

In our admin area we can manage all purchases, products, coupons and more.

Architecture

Clean architecture: business logic and data access clearly separated from the UI.

Actions

Server Actions with auth, validation, revalidation

Use cases

Business logic orchestrated (e.g. upload workflows)

DB layer

Encapsulated data access layer

Performance & search

🔍 PostgreSQL full-text search

  • • GIN indexes for multilingual search
  • • Composite indexes for filter combinations
  • • Optimized queries with EXPLAIN ANALYZE

📊 Performance tracking

  • • PostHog events (duration_ms, results_count)
  • • A/B testing of components (e.g. AI scanner)
  • • Measurable instead of gut feeling
Live demo at passpad.de