AI Finance Tracker

Built a full-stack AI finance application using React, Node.js, and PostgreSQL to track expenses, budgets, and spending, with secure user authentication and account management via Supabase, including protected routes, session handling, and user-specific data isolation. Developed a Python-based AI backend (FastAPI) that leverages Pandas for data analysis and OpenAI GPT-3.5-turbo for natural language processing, implementing a hybrid AI system where Pandas DataFrames process financial data (calculating category breakdowns, monthly trends, and budget comparisons) while OpenAI API generates conversational, context-aware responses with personalized financial insights based on real-time user data.

Overview

The AI Finance Tracker is a comprehensive financial management application that combines modern web technologies with artificial intelligence to provide users with an intuitive way to manage their finances. The application allows users to track expenses, manage budgets, and get personalized financial insights through natural language interactions.

Key Features

• Secure user authentication and account management via Supabase
• Protected routes, session handling, and user-specific data isolation
• Natural language expense tracking and queries
• Automated budget management and alerts
• Interactive spending visualizations
• Hybrid AI system combining Pandas data processing with OpenAI GPT-3.5-turbo
• Real-time financial insights based on user data
• Category breakdowns, monthly trends, and budget comparisons
• Conversational, context-aware AI responses

Technology Stack

Frontend

• React - Modern UI framework for building interactive user interfaces
• Node.js - JavaScript runtime for server-side operations

Backend

• Python - Core programming language for AI backend
• FastAPI - High-performance web framework for building APIs
• OpenAI API - Natural language processing and AI capabilities
• Pandas - Data manipulation and analysis

Database & Authentication

• PostgreSQL - Relational database for storing financial data
• Supabase - User authentication, account management, protected routes, and session handling

Deployment

• Docker - Containerization for consistent deployment
• Vercel - Cloud hosting platform

Implementation Highlights

The application features a modular architecture with a React frontend communicating with a Node.js API server, which in turn interfaces with a Python-based AI service. The AI backend processes natural language queries using the OpenAI API and performs data analysis with Pandas to generate personalized financial insights.

All components are containerized using Docker, ensuring consistent deployment across different environments. The PostgreSQL database securely stores user financial data with proper authentication and authorization mechanisms.