PetMatch AI

PetMatch AI – Find your perfect pet with AI-powered breed matching, smart profiles, and a fun points-based rewards system.

Comment

🐾 Inspiration

Choosing the right pet can be overwhelming—especially for first-time owners. Many adopt based on looks, not lifestyle fit, leading to unhappy outcomes. We wanted to build a tool that uses AI to match people with pets based on compatibility and reward them for positive engagement.

🔍 What it does

PetMatch AI recommends the ideal pet breed using user preferences. It includes secure authentication, user profiles, a tiered points/rewards system, and coupon redemptions. Users earn points for actions and climb tiers from Bronze to Diamond. Admins can manage users and rewards.

🏗️ How we built it

We built the frontend using Next.js 14 (App Router), TypeScript, and Tailwind CSS for a fast, modern UI. The backend uses Supabase (PostgreSQL, Auth, Realtime). We wrote custom SQL functions for adding points, redeeming coupons, and tracking user tiers. Authentication includes email/password and OAuth (Google, GitHub). All data is protected with Row Level Security (RLS).

🧱 Challenges we ran into

  • Setting up and debugging OAuth redirection
  • Writing secure and efficient SQL functions for point logic
  • Balancing RLS policies with custom access needs (e.g., admins)
  • Designing a responsive layout that feels native on mobile
  • Handling edge cases like coupon re-use and expired codes

🏆 Accomplishments that we're proud of

  • Built a fully functional AI-powered pet matching platform
  • Implemented a scalable and gamified reward system
  • Secure user data isolation using RLS
  • Real-time point updates and user tiering
  • Clean, responsive, and accessible UI

📚 What we learned

  • Managing user state and roles with Supabase
  • Writing production-grade SQL functions
  • Creating and testing RLS policies
  • Structuring scalable database schemas
  • Making secure and beautiful UIs using shadcn/ui and Tailwind

🚀 What's next for PetMatch AI

  • Integrating a machine learning model for smarter breed recommendations
  • Adding pet profiles and adoption listings from local shelters
  • Launching a mobile app version (Flutter or Expo)
  • Enabling pet care tips and daily engagement tasks for more rewards
  • Monetizing via premium coupons or partner vet clinics

Built With

  • bolt
  • database
  • flux
  • lucide-react
  • nextjs
  • openai
  • radix-ui
  • shadcn/ui
  • supabase
  • tailwind-css
  • typescript
Share this project:

Updates