Drashti Senjaliya@dras

Resume Evaluator is an intelligent, rule-based web application to enable recruiters to shortlist resumes automatically with quick, clear logic—without the need to depend on complicated AI or machine learning models. The app, developed in Python and Streamlit using Trae AI IDE , enables HR professionals to upload multiple resumes as PDF files and get auto-extracted important information like the candidate name, contact number, total experience, skills, projects, achievements, and desired salary. At its center is a strong resume parsing component that utilizes pdfplumber for PDF text extraction and regular expressions for data parsing. While black-box AI programs are opaque, Resume Evaluator employs explicit and tunable rules to determine skills, recognize experience patterns, and extract relevant project or achievement information. This provides transparency, complete logic control, and straightforward debugging support for real-world HR processes. Recruiters can enter job-specific needs like preferred skills, minimum experience in years, and budgeted salary ranges. The application then analyzes each resume against these parameters, rating candidates with a user-definable formula. The score takes into account experience, number of matched skills, number of skills, number of projects, and accomplishments. All matched resumes are ordered and presented in an editable table, along with an interactive, expandable view for candidate-by-candidate detailed analysis. Resume Evaluator is perfect for HR departments, startups, or college placement cells seeking a lightweight, smart resume sifting software. It greatly minimizes manual effort, enhances consistency, and accelerates hiring choices making the screening process smart, quick, and efficient. Our goal is to build a platform for all managers or any person willing to hire the right candidates, while still fairly considering every candidate so that you won't miss out any.

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