I Built an AI Resume Analyzer in Spring Boot Instead of Another CRUD Project

After finishing my previous AI Support Widget project, I wanted to build something that solved a different real-world problem.

Most developers have built a Todo app, an Employee Management System, or another CRUD project.

I wanted to build something people could actually use.

So I spent the last few weeks building an AI-powered Resume Analyzer using Spring Boot.

## The idea

Whenever I apply for jobs, I usually wonder:

• Is my resume ATS friendly?
• Which keywords am I missing?
• Which resume version is better?
• How can I improve my chances before applying?

There are plenty of online tools, but I wanted a self-hosted application that I fully controlled.

## Tech Stack

• Java 17
• Spring Boot 3
• Spring Security
• Spring Data JPA
• Thymeleaf
• MySQL
• OpenAI API

## What it does

Instead of simply uploading a resume and getting one score, the application provides multiple AI-powered features.

### ATS Resume Analysis

The application analyzes a resume against a job description and generates:

• ATS score
• Resume strengths
• Weaknesses
• Missing keywords
• Resume improvement suggestions

### AI Resume Rewrite

Instead of manually editing bullet points, the application rewrites the resume while preserving the candidate's actual experience.

The goal isn't to invent achievements.

It's to improve clarity and ATS readability.

### Resume Comparison

One feature I personally found useful was comparing two versions of the same resume.

Sometimes changing only a few bullet points increased the ATS score significantly.

### Resume Versioning

Rather than replacing previous analyses, every analysis is saved.

This allows users to compare improvements over time.

### AI Interview Preparation

After analyzing the resume, the application can generate interview questions based on:

• Resume
• Skills
• Experience
• Job Description

This makes the tool useful even after the ATS analysis is complete.

### Dashboard

The application also includes a dashboard showing:

• Previous analyses
• Average ATS score
• Highest score
• Resume history
• Trends over time

## Challenges

One interesting challenge was balancing AI output with predictable scoring.

Large Language Models are creative, but ATS scoring should feel consistent.

I ended up combining deterministic scoring with AI-generated explanations so that users receive both a measurable score and useful feedback.

## What I intentionally didn't build

One thing I deliberately left out was payment gateway integration.

The application already supports usage limits and user plans, but checkout integration (Stripe/Razorpay) is something I'd rather let developers integrate based on their own business needs.

## Lessons Learned

Building AI products isn't just about calling an LLM.

Most of the work is actually:

• Prompt engineering
• Designing good workflows
• Managing user data
• Producing useful outputs
• Creating a smooth user experience

Those parts took far longer than integrating the OpenAI API itself.

## Final Thoughts

This project taught me much more than another CRUD application ever could.

I'm now building a collection of AI-powered Spring Boot applications focused on solving real business problems instead of tutorial-style examples.

If you're building AI products with Java or Spring Boot, I'd love to hear what you're working on.

### Source Code

I packaged this project as a complete Spring Boot source code product with documentation, database scripts, API collection, installation guide, and production-ready architecture.

If you'd like to build on top of it instead of starting from scratch, you can check it out here:

👉 https://swarnalata25.gumroad.com/l/resumeiq-ai

I'd also love your feedback on what features you'd add next.