Personal Finance & Expense AI Assistant — MERN + AI/ML powered app that helps users track, categorize, analyze, and forecast their spending.

🔗 Live Demo: RupeeRadar AI
👩‍💻 Created by Aditi Kesharwani — © Copyright Infringement

✅ CSV Upload – Import transactions from bank statements
✅ SMS/UPI Parser – Paste raw SMS & auto-extract transactions
✅ Auto Categorization – Food, Travel, Shopping, Utilities, Subscriptions, Housing, etc.
✅ Smart Insights – Subscription spend, high spend alerts, monthly net, savings tips
✅ Budgets – Set category budgets & see real-time spent vs. limit (with ✅ Under / ⚠️ Near / ❌ Over status)
✅ Spending Visualization – Interactive Pie/Bar charts with category-wise breakdown
✅ 6-Month Balance Forecast – Projected balance trend using monthly net
✅ Gamification – Budget score and levels for engagement
✅ Authentication – JWT-based login/signup (secure password hashing with bcrypt)
✅ Deployed – Backend + frontend deployed on Render

Frontend: React (Vite), Axios, Recharts, React Router
Backend: Node.js, Express.js, Multer (CSV upload), JWT Auth, Bcrypt
Database: MongoDB (Mongoose ODM, compound indexes)
Deployment: Render (client + server), MongoDB Atlas

Clone the repo:

git clone https://github.com/Aditi2354/RupeeRadar-AI.git
cd RupeeRadar-AI
🔹 Server Setup
bash
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cd server
npm install
# create .env file
MONGO_URI="your-mongodb-connection-string"
JWT_SECRET="your-secret-key"
PORT=4000

npm run dev
🔹 Client Setup
bash
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cd client
npm install
# create .env file
VITE_API_URL="http://localhost:4000/api"

npm run dev
🧩 Project Architecture
bash
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RupeeRadar-AI/
│── client/        # React frontend
│── server/        # Express backend
│── README.md
🔮 Future Improvements
AI/ML-based categorization using embeddings

Advanced forecasting (Prophet/ARIMA)

Multi-currency + savings goals

Bank API integration for real-time sync

✨ Author
👩‍💻 Aditi Kesharwani
📌 MERN Developer | Data Enthusiast | Building AI-powered Finance Tools