AI-Powered Resume Analyzer Development

Project Overview The AI-Powered Resume Analyzer is a full-stack MERN application that helps job seekers evaluate and improve their resumes using Artificial Intelligence. Instead of providing only a basic ATS score, the application performs a comprehensive analysis of resume content, identifies weaknesses, recommends improvements, compares the resume with job descriptions, and generates an AI-based report to maximize interview opportunities. The primary objective is to simulate how modern Applicant Tracking Systems (ATS) and recruiters evaluate resumes while also providing personalized recommendations generated by a Large Language Model (LLM). Problem Statement Many fresh graduates submit the same resume to every company without customizing it. This creates several problems: Poor ATS compatibility Missing technical keywords Weak project descriptions Generic summaries Improper formatting Low recruiter visibility Most online ATS checkers provide only a score but fail to explain: Why the score is low Which skills are missing How to improve each section How well the resume matches a specific job The AI Resume Analyzer solves these problems through intelligent resume analysis and AI-generated recommendations. Objectives The project aims to: Analyze uploaded resumes automatically Extract structured information from PDF files Compare resumes against job descriptions Calculate ATS compatibility Identify missing technical skills Suggest stronger resume content Generate personalized AI feedback Produce downloadable reports Technology Stack Frontend React.js React Router Tailwind CSS Axios React PDF Viewer Backend Node.js [login to view URL] REST APIs Database MongoDB Mongoose ODM Artificial Intelligence LLM API (used for resume evaluation and enhancement) Natural Language Processing techniques Prompt Engineering File Processing PDF Parser Resume Text Extraction Other Tools JWT Authentication Git & GitHub A MERN architecture allows JavaScript to be used across the full stack, simplifying development and enabling scalable applications.

Project ID: 40538702