Popular GitHub Repositories for Recruitment

Advising App by Canyon GBS is an AI-powered conversational assistant for staff, student success platform, and recruitment CRM designed specifically for colleges and universities to enhance student engagement and drive institutional success.

This is a project aiming to optimize the recruitment process. It integrates an advanced Applicant Tracking System with Google Gemini Pro, streamlining resume parsing, keyword matching, and candidate evaluation for an efficient end-to-end solution in talent acquisition.

Revolutionize your recruitment process with this cutting-edge proof of concept! Developed from the inspiration of josephkearney91's LinkedIn scraping project, this advanced tool harnesses the capabilities of the OpenAI API (Chat GPT) to craft and send customized messages to prospective candidates across various languages.

This tool aims to simplify the process of reviewing job applicants' resumes, extracting relevant data, and making data-driven decisions in recruitment using NLP.

An interactive model built mainly using unsupervised learning techniques. Useful for player scouting and recruitment in football.

A multi-agent recruitment assistant that leverages Microsoft AutoGen framework to streamline hiring processes. The system employs specialized AI agents working in concert to automate resume screening, candidate evaluation, and interview preparation.

A smart, responsive, and fully-functional web application designed to **transform job applications and recruitment processes** using the power of AI.

Enhancing Recruitment Process using Text Mining and Machine Learning (Resume Mining) using Graph Database Neo4j

This project is an AI Recruitment System designed to accelerate the hiring process for HR and technical recruiters.

RucRut is an AI-powered recruitment system that streamlines the hiring process by automatically generating interview questions, evaluating candidate responses, and providing real-time feedback. It leverages Natural Language Processing (NLP) to enhance recruitment efficiency for job providers and candidates.

The AI-Powered Job Portal project is a full-stack web application designed to facilitate job searching and job posting. This portal offers advanced features for both job seekers and recruiters, including AI-generated job descriptions, providing a seamless and efficient experience for job hunting and recruitment. The application is built with robust

Join our Ship-Every-Friday Squad! We're looking for MERN + Python developers who treat AI tools as first-class teammates. Apply by submitting a PR - our bot analyzes your GitHub profile and scores based on GenAI usage (50%) and open source contributions (30%). Ship to millions every week!

This project is an AI-powered cold email generator designed to craft personalized and professional email templates for outreach. Built with advanced natural language processing (NLP) models, it enables users to input key details and generate tailored emails for various use cases, such as sales, networking, or recruitment.

An AI-powered tool that ranks resumes based on a job description using NLP and semantic similarity with Sentence Transformers.

An example recruitment chat bot

SATS (Smart Applicant Tracking System) is an advanced recruitment tool that uses contextual understanding and comprehensive analysis to evaluate candidates based on education, experience, and expertise. It includes features like contextual analysis and a leaderboard system, making recruitment more efficient and accurate.

AI-Powered Recruitment: Simplifying Talent Acquisition.

An AI-driven recruitment system using Llama 3.x to automate and enhance key stages of the hiring process.

"Intellect Hire: The AI Talent Curator" streamlines hiring by extracting resume details, prompting users to upload resumes, matching candidates with jobs, and evaluating candidate suitability, enhancing recruitment efficiency and accuracy.

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.