Building an AI-Powered Expense Tracker with Spring Boot, Spring AI, and Google Gemini

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Managing personal finances is one of the most common challenges in today’s world. While traditional expense trackers record spending, they don’t provide actionable insights.
That’s where AI-powered applications step in.

In this blog, I’ll walk you through a project where I built an Expense Tracker integrated with Google Gemini AI using Spring Boot and Spring AI.
This application not only tracks expenses but also provides real-time cost-saving suggestions and insights powered by Gemini.

🚀 Project Overview

The AI Expense Tracker is a backend application that:

Records user expenses (category, amount, description, date).

Stores data in a relational database (MySQL).

Provides JWT-secured APIs for expense management.

Integrates with Google Gemini AI using Spring AI.

Generates personalized suggestions to help reduce unnecessary spending.

👉 Imagine logging your food, shopping, and entertainment expenses, and the system automatically tells you:

“Cut down on shopping and try cooking at home more often — you can save ₹3,000 this month.”

That’s the power of combining Spring Boot + AI.

🛠️ Tech Stack

Java 17

Spring Boot 3

Spring Security + JWT (for authentication)

Spring AI (to connect Gemini with Spring Boot)

Google Gemini API (AI model for insights)

Hibernate + JPA (ORM)

MySQL (database)

Postman (API testing)

⚙️ Architecture

Expense Entity

Stores data like amount, category, description, date, and user reference.

Repository Layer

Fetches user expenses from the MySQL database.

Gemini Integration

Expense data is sent to Gemini API.

Gemini analyzes patterns and returns actionable suggestions.

Controller Layer

REST endpoints expose expense tracking and AI analysis features.

🔑 Key Features

✔️ Track Expenses – Add, update, and fetch expenses.
✔️ AI-Powered Suggestions – Get real-time insights on saving money.
✔️ JWT Security – Secure access to APIs.
✔️ Postman Testing – Simple interface for testing endpoints.
✔️ Custom Prompts – Tailor AI responses to be short, simple, and actionable.

🧩 Example Workflow

User adds expenses:

[
{ "category": "Food", "amount": 12000, "description": "Restaurant & groceries" },
{ "category": "Shopping", "amount": 8000, "description": "Clothes & shoes" },
{ "category": "Transport", "amount": 5000, "description": "Cab & fuel" }
]

System prepares AI prompt:

Here are the user’s expenses:

  • Food: 12000
  • Shopping: 8000
  • Transport: 5000

Please suggest 3-5 short, simple, actionable tips to save money.

Gemini AI Response:

  • Cook at home instead of frequent dining out.
  • Delay non-essential shopping purchases.
  • Use public transport or carpool to reduce travel costs.
  • Cancel unused subscriptions.

📊 Why This Project Matters

💡 Traditional expense trackers = record keeping only.
💡 AI Expense Tracker = real-time insights.

By integrating AI, we shift from “What I spent” → “How I can save.”

This project is a great example of practical AI integration into real-world apps using Spring Boot.

🎥 Project Demo

👉 Watch the full demo on YouTube here:
Youtube Video

✅ That’s it! We’ve combined Spring Boot, Spring AI, and Gemini to build something genuinely useful and future-proof.

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