A full-stack cryptocurrency trading and investment platform for Indian retail investors. Real-time trading, portfolio tracking with live P&L, AI-powered insights, and INR wallet management.
Demo project — Stripe and Razorpay run in test mode. No real money is involved.
Live: https://trade-chi-five.vercel.app GitHub: https://github.com/Aadarsh-max/Trade
- JWT authentication with access and refresh token rotation
- INR wallet with deposit and withdrawal support
- Stripe (international) and Razorpay (India) payment integration in test mode
- Real-time crypto price ticker and candlestick charts
- Market and limit order placement with a custom matching engine
- Live order-fill and rejection notifications via WebSocket
- Portfolio holdings with unrealized and realized P&L in INR
- Allocation breakdown with visual charts
- AI chat assistant aware of your real portfolio context
- News sentiment analysis powered by Groq
- Daily AI-generated market summaries
- Persistent notification system for all trade and wallet events
- Fully responsive dark-first UI
- Node.js, Express
- PostgreSQL via Prisma ORM
- MongoDB
- Redis
- Socket.io
- BullMQ
- Groq API (Llama 3.3 70B)
- Stripe, Razorpay
- Zod, Winston, JWT, Bcrypt
- React 18, Vite
- Tailwind CSS v4
- Zustand
- Framer Motion
- lightweight-charts (TradingView)
- Recharts
- Socket.io client
- Axios
- Frontend — Vercel
- Backend — Render
- PostgreSQL — Neon
- MongoDB — MongoDB Atlas
- Redis — Upstash
- Stateless API servers — all session state in Redis, horizontally scalable
- ACID transactions — every wallet and trade operation is atomic in Postgres
- Idempotency keys — all payment and wallet endpoints are safe against duplicate requests
- Background workers — BullMQ runs as a separate process, async tasks never block the API
- Redis pub/sub — price updates from the polling job broadcast to all Socket.io clients
- Currency isolation — market prices are USD, wallet is INR, conversion at execution time using live exchange rates with a 5-minute cache
- Separation of stores — financial data in Postgres, AI history and logs in MongoDB
Aadarsh GitHub