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AI-driven recruitment management system streamlining candidate evaluation through multi-round interviews, automated analytics, and real-time collaboration.

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iRecruit360

iRecruit360 is an innovative recruitment management system designed to streamline and enhance the hiring process. By leveraging AI and machine learning, it provides a comprehensive solution for evaluating and managing candidates through multiple interview rounds.

Table of Contents

Features

  • Candidate Account Management: Candidates can create accounts and manage their profiles.
  • Applicant Tracking: Track applicant profiles, resumes, and status throughout the recruitment process.
  • Interview Management: Conduct and manage interviews in three rounds:
    • Round 1: Personality analysis using K-means clustering.
    • Round 2: Video recording analysis.
    • Round 3: Resume extraction and automatic question generation.
  • Team Collaboration: Enable team collaboration with multi-user access and customizable permissions.
  • Analytics and Reporting: Utilize large language models to produce analytics and reports on candidate performance.
  • Email Automation: Automated email notifications for HR to streamline communication.

Architecture

Frontend

  • Developed using Next.js, Tailwind CSS, and TypeScript.
  • Provides an intuitive and responsive interface for candidates and recruiters.

Backend

  • Developed using Python and Flask.
  • Handles business logic, data processing, and storage.
  • Integrates with Firebase for real-time database management.

AI Integration

  • K-means Clustering: Used for personality analysis in the first interview round.
  • Large Language Models: Employed to generate performance reports and analytics.

Installation

Prerequisites

  • Node.js
  • Python 3.x
  • Firebase account

Steps

  1. Clone the repository:

    git clone https://github.com/MuhammedBasith/iRecruit360.git
  2. Navigate to the project directory:

    cd iRecruit360
  3. Install frontend dependencies:

    cd frontend
    npm install
  4. Start the frontend server:

    npm run dev
  5. Install backend dependencies:

    cd ../iRecruit360-backend
    pip install -r requirements.txt
  6. Set up environment variables: Create a .env file in the iRecruit360-backend directory and add your environment variables as per the .env.example file.

  7. Start the backend server:

    python server.py

Usage

  1. Access the application: Open a web browser and go to http://localhost:3000 for the frontend.
  2. Sign in or create an account: Begin by signing in or creating a new account to start using the platform.
  3. Explore features: Utilize the dashboard to manage candidates, conduct interviews, and review analytics.

Project Structure

iRecruit360/
│
├── frontend/
│   ├── public/
│   ├── src/
│   ├── package.json
│   └── ...
│
├── iRecruit360-backend/
│   ├── irecruit360/
│   ├── manage.py
│   ├── requirements.txt
│   └── ...
│
├── .gitignore
└── README.md

Contributing

Contributions are welcome! Please follow these steps:

  1. Fork the repository.
  2. Create a new branch.
  3. Make your changes.
  4. Submit a pull request.

License

This project is licensed under the MIT License. See the LICENSE file for more details.

Contact

For any inquiries or support, please contact Muhammed Basith.

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AI-driven recruitment management system streamlining candidate evaluation through multi-round interviews, automated analytics, and real-time collaboration.

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