Unsupervised AI candidate ranking system — hybrid rule-based scoring + semantic embeddings over 100K profiles. Built for the Redrob AI challenge (India Runs Hackathon 2025).

VitaSort is an AI-powered resume screening and ranking tool that revolutionizes hiring by leveraging machine learning for precise candidate evaluation. Built with Streamlit, it offers real-time PDF resume analysis, TF-IDF vectorization, and cosine similarity scoring, complemented by advanced visualizations like radar charts and skills heatmaps.

Enterprise-grade AI-powered Multi-Tenant Applicant Tracking System (ATS) for HR automation intelligently parse, score, and rank candidates using semantic AI for faster, smarter hiring decisions.

TalentTrack is an open‐source recruitment analytics web application built with Flask and Python. It leverages advanced machine learning techniques—such as Product Quantization (PQ) for candidate ranking and SHAP for model interpretability—to help HR teams and recruitment professionals identify high-quality candidates efficiently.

AI resume screening and candidate ranking system using Python, FastAPI, and semantic skill matching to analyze resumes and compare candidates against job descriptions.

AI Hiring Tool using React, Flask, OpenAI, and Pinecone. Recruiters input a job description, and the app parses it, scores candidate resumes or LinkedIn profiles, and generates tailored interview questions—showcasing AI integration, product intuition, and modern recruiting automation.

AI-powered ATS simulation that screens, scores, and ranks resumes using TF-IDF, cosine similarity, and skill matching. Features Streamlit recruiter dashboard, NLP analytics, automated shortlisting, and CSV/JSON reporting.

This project simulates an AI-powered resume screening system that extracts and analyzes candidate information such as skills, experience, and tools.

Resume Ranking System is a web application developed using Python, Flask, HTML, CSS, and SQLite that ranks resumes based on skill matching with job descriptions.

Explainable AI-powered candidate ranking system for the Redrob India Runs Data & AI Challenge.

This project is a sophisticated, production-ready Candidate Filtering & Ranking System designed to streamline the recruitment process. Leveraging Next.js 14 and TypeScript, it automates the evaluation of candidates against Job Descriptions (JDs) using a weighted algorithm.

Adaptive multi-star candidate ranking system using deterministic scoring + relevance feedback with bias-aware filtering.

AI Resume Screening System using Python & ML

A recruiter-centric candidate ranker that evaluates full career histories, filters out honeypots, and generates structured reasoning for the Senior AI Engineer role

🎯 Intelligent resume analysis and candidate ranking system with advanced fraud detection capabilities. Features AI-powered analysis, white font detection, smart ranking algorithms, and comprehensive ATS gaming prevention.

Automated resume screening & candidate ranking tool — paste a job description, upload resumes (PDF/DOC/DOCX), and get each candidate scored 0–100 with ranked results. Built with Next.js, FastAPI, PostgreSQL.

TalentMatch AI is an intelligent recruitment platform that automates resume screening, candidate ranking, ATS scoring, skill extraction, and job matching using NLP, Machine Learning, BERT embeddings, and semantic search.

India Runs — intelligent candidate discovery & ranking engine, built for the Redrob AI hackathon.

AI-powered resume screening system using NLP embeddings and hybrid scoring to rank candidates based on skills, domain, experience, and semantic similarity.

Full-stack AI resume screening system with semantic search, vector embeddings (Pinecone), LLM scoring via HuggingFace, and Gmail OAuth integration to automate candidate shortlisting.