AI-powered resume intelligence and candidate matching platform for resume parsing, candidate normalization, ranking workflows, external submissions, MFA support, and recruitment automation.

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

AI-powered candidate ranking system using Sentence Transformers, semantic search, and behavioral scoring.

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.

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.

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

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.

A production-grade, fully-offline Candidate Discovery and Ranking system built for the Redrob Intelligent Candidate Discovery & Ranking Challenge.

AI-powered candidate discovery and ranking system using BGE embeddings, FAISS vector search, and hybrid multi-signal ranking.

Premium CPU-only AI ranking system for Redrob India Runs Track 1 Intelligent Candidate Discovery

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.

Multi-signal AI ranking engine for candidate discovery — semantic + role-fit + skill depth + behavioral + career trajectory scoring over 100K profiles, FAISS-indexed, CPU-rankable in <5 min.

AI Resume Screening System using Python & ML

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.

HireSense AI is an intelligent candidate ranking system that processes candidate profiles and ranks them against job requirements using explainable AI. Built for the INDIA.RUNS Data & AI Challenge, it combines a powerful Python backend with a modern React frontend.

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 candidate ranking system — hybrid retrieval, cross-encoder reranking, and multi-signal scoring for the Redrob Data & AI Challenge 2026