🤖💰 Building an AI-Powered Expense Tracker with Modern Web Technologies
🔥 Hono + ⚡ Next.js + 🤖 OpenAI powered expense tracker with natural language processing! Featuring real-time AI chat, smart tagging, and modern full-stack architecture.
🎯 Project Overview
The expense tracker is a full-stack web application that allows users to manage their expenses through both traditional UI interactions and an intelligent chat interface. Users can create, categorize, search, and analyze their expenses using natural language commands, making financial management as simple as having a conversation.
Key Features
- AI-Powered Chat Interface: Natural language expense management through OpenAI integration
- Smart Tagging System: Organize expenses with custom tags for better categorization
- Real-time Insights: Get instant summaries and analytics of spending patterns
- Secure Authentication: User management powered by Clerk
- Responsive Design: Beautiful, modern UI that works across all devices
- Tool Calling: AI can directly interact with the database through structured function calls
⚡ Tech Stack Showcase
Modern Horizontal Architecture: This streamlined stack flows from Hono's ultra-fast Edge APIs → Next.js responsive frontend → OpenAI intelligent conversations, supported by Turso's global SQLite performance, Drizzle's type-safe operations, Clerk's secure authentication, and Vercel AI SDK's seamless integration.
🛠️ Tech Stack
The project leverages a modern, type-safe tech stack designed for performance and developer experience:
Frontend
- Next.js 15 - React framework with App Router for optimal performance
- React 19 - Latest React features for modern component development
- Tailwind CSS - Utility-first CSS framework for rapid UI development
- Shadcn Components - Customizable Components
- Vercel AI SDK - Seamless AI integration with streaming responses and tool calling
Backend
- Hono - Ultra-fast web framework for the Edge
- Turso (LibSQL) - Distributed SQLite database for global performance
- Drizzle ORM - Type-safe database operations with excellent TypeScript support
- Clerk - Complete authentication and user management solution
AI & Integration
- OpenAI GPT-4 - Advanced language model for natural language processing
- AI SDK Tools - Structured function calling for database operations
- Zod - Runtime type validation for API endpoints
🏗️ Architecture Deep Dive
Database Design
The application uses a clean, normalized database schema with three main entities:
-- Expenses table
expenses: id, title, amount, userId, createdAt
-- Tags table
tags: id, tagName, userId, createdAt
--- Chat threads table
chat_threads: user, thread_id, created_timestamp
--- Chat Messages
chat_messages: user, thread_id, message, role(user,AI)
This design allows for flexible tagging while maintaining data integrity and enabling efficient queries and as well integrating with Agentic approach
API Architecture
The backend is built with Hono, providing a lightweight yet powerful API layer:
// Modular route structure
const apiRoutes = app
.route("/expenses", expenseRoute)
.route("/tags", tagRoute)
.route("/credits", creditsRoute)
.route("/chat", chatRoute);
Each route is properly authenticated using Clerk middleware, ensuring users can only access their own data.
AI Integration
The chat interface uses the Vercel AI SDK with structured tool calling:
const result = streamText({
model: openai('gpt-4o-mini'),
system: `You are a helpful AI assistant for expense tracking...`,
messages,
tools: {
create_expense: tool({
description: 'Create a new expense entry',
parameters: z.object({
title: z.string(),
amount: z.number(),
tagNames: z.array(z.string()).optional(),
}),
execute: async ({ title, amount, tagNames }) => {
// Direct database interaction
},
}),
// Additional tools for search, summary, insights, etc.
},
});
🤖 AI-Powered Features
Natural Language Expense Creation
Users can create expenses using natural language: - "Add $25 for groceries" - "I spent $15 on lunch today" - "Record a $50 expense for gas with transportation tag"
The AI extracts relevant information and creates structured database entries.
AI-powered chat interface allowing natural language expense creation
Real-time expense creation and confirmation showing the AI successfully processed the request
Intelligent Search and Filtering
The chat interface supports complex queries: - "Show me all expenses over $20 from last month" - "Find my restaurant expenses" - "What did I spend on groceries this week?"
Real-time Analytics
Users can get instant insights: - "Give me my expense summary" - "Show insights for this month" - "What's my daily average spending?"
Smart Tag Management
The AI can automatically suggest and create tags based on expense descriptions, improving organization over time.
🎨 User Experience
Chat Interface Design
The chat interface features: - Streaming responses for real-time feedback - Tool execution visualization showing what actions the AI is performing - Collapsible technical details for transparency - Quick action buttons for common operations - Beautiful message bubbles with timestamps
Traditional UI Components
Beyond the chat interface, the app includes: - Expense list with filtering and sorting - Tag management with CRUD operations - Analytics dashboard with visual insights - User profile and settings
🔒 Security & Authentication
Security is paramount in financial applications:
- Clerk Authentication: Secure user management with social logins
- Row-level security: Users can only access their own data
- API rate limiting: Credit system to prevent abuse
- Input validation: Zod schemas for all API endpoints
- HTTPS everywhere: Secure data transmission
🚀 Performance Optimizations
Database Performance
- Indexed queries for fast expense retrieval
- Efficient joins using Drizzle ORM
- Connection pooling with Turso
Frontend Performance
- Server-side rendering with Next.js App Router
- Optimistic updates for better UX
- Code splitting for smaller bundle sizes
- Image optimization with Next.js built-ins
AI Performance
- Streaming responses for perceived speed
- Function calling for structured operations
- Context optimization to reduce token usage
📊 Real-World Usage
The application handles common expense management scenarios:
- Daily Expense Logging: Quick entry through chat or forms
- Monthly Reviews: AI-generated summaries and insights
- Budget Tracking: Tag-based categorization for budget analysis
- Receipt Processing: Natural language description parsing
- Expense Reporting: Export capabilities for tax purposes
🔮 Future Enhancements
Planned improvements include:
- Add credits for LLM usage: Track the number of credits used by the LLM.
- Budget alerts: Proactive spending notifications
💡 Key Learnings
Building this project taught me valuable lessons:
- AI Integration: Structured tool calling is more reliable than prompt engineering alone
- Type Safety: Zod + TypeScript catches errors before they reach production
- User Experience: Streaming responses make AI interactions feel more natural
- Database Design: Proper normalization prevents data inconsistencies
- Authentication: Clerk simplifies complex user management scenarios
🎉 Conclusion
This AI-powered expense tracker demonstrates how modern web technologies can create powerful, user-friendly applications. By combining the intelligence of AI with robust backend architecture and beautiful frontend design, we can build tools that genuinely improve people's daily lives.
The project showcases the potential of conversational interfaces in financial applications, making expense management accessible to users regardless of their technical expertise. As AI continues to evolve, we can expect even more sophisticated interactions and insights.
Want to see the code? Check out the GitHub repository or try the live demo. Feel free to reach out if you have questions about the implementation or want to discuss similar projects!
🏷️ Tags
#AI #NextJS #Hono #TypeScript #FullStack #ExpenseTracker #OpenAI #Turso #ModernWeb