AI-Powered Inclusive Career Development Platform
Equirk is an AI-powered career development platform that provides personalized guidance for everyone, regardless of ability. Using AI and Internet Computer (ICP), it combines personalized career roadmaps with accessibility-first design to democratize career development.
Career platforms exclude people with disabilities and lack personalized guidance. Equirk creates an inclusive AI-powered platform using Google Gemini for personalized roadmaps and accessibility-focused job matching on ICP blockchain.
| Name | Role |
|---|---|
| Muhammad Karov Ardava Barus | Lead, AI/ML Engineer, Backend Developer |
| Casta Garneta | UI/UX Designer |
| Farrel Ardya Ghalyndra | Fullstack Developer |
| Putu Padmanaba | AI/ML Engineer |
- 🤖 Personalized Career Roadmaps powered by AI, adapting to individual skill levels.
- ♿ Accessibility-First Design with specialized guidance for people with disabilities.
- 📄 Resume Analysis & Learning Paths integrated directly into the platform.
- 🎯 Intelligent Job Matching with transparency and inclusivity at the core.
- 🔐 Decentralized Web using Internet Computer to ensure users own their career data.
Frontend:
- React 19.1.0 with Vite
- Tailwind CSS 4.1.11
- Framer Motion for animations
- React Router DOM for navigation
- PDF.js for resume processing
Backend:
- Node.js with Express
- Google Gemini LLM (@langchain/google-genai)
- PDF parsing with pdf-parse
- Multer for file uploads
- Python Flask (for ML recommendation system)
Machine Learning:
- Python 3.8+
- Flask for ML API
- Pandas, NumPy for data processing
- Scikit-learn for job matching algorithms
Blockchain:
- Internet Computer (ICP)
- DFX for canister deployment
System Requirements:
- Node.js 18+
- Python 3.8+
- npm or yarn
- pip (Python package manager)
- DFX SDK (for ICP deployment)
API Keys Required:
- Google Gemini API Key (for AI features)
git clone https://github.com/Ardavaa/equirk.git
cd equirkCreate .env file in the backend directory:
GEMINI_API_KEY=your_gemini_api_key_here
# or
GOOGLE_API_KEY=your_gemini_api_key_hereCreate and activate virtual environment:
# Create virtual environment
python -m venv venv
# Activate virtual environment
# On Windows:
venv\Scripts\activate
# On macOS/Linux:
source venv/bin/activate
# Install Python dependencies
pip install -r backend/requirements.txtBackend (Node.js):
cd backend
npm installFrontend:
cd frontend
npm installStart Python Flask Recommender (Terminal 1):
# Make sure virtual environment is activated
cd backend
python flask_recommender.pyFlask recommender will run on http://localhost:5000
Start Node.js Backend Server (Terminal 2):
cd backend
node server.jsBackend will run on http://localhost:3001
Backend will run on http://localhost:3001
Start Frontend Development Server (Terminal 3):
cd frontend
npm run devFrontend will run on http://localhost:5173
Access the Application:
- Frontend:
http://localhost:5173 - Node.js Backend:
http://localhost:3001 - Flask ML Service:
http://localhost:5000
Build Frontend:
cd frontend
npm run buildStart DFX and Deploy:
dfx start --background
dfx deployWe are building towards an end-to-end career development ecosystem, including:
- 📄 AI CV & Cover Letter Builder for instant professional documents
- 🧩 Gamified Skill Assessments to engage users in identifying strengths
- 📚 Micro-Learning Modules to quickly fill skill gaps
- 🔗 Mentorship & Networking Hub to connect users and mentors
- 📊 Career Analytics Dashboard for tracking growth and opportunities
- 🌍 Enhanced Accessibility (voice-to-text, screen reader support, sign-language AI assistant, multilingual features)
- Pitch Deck: Watch here
- Demo: Watch here
This project is licensed under the MIT License - see the LICENSE file for details.
For questions, issues, or feedback:
- Open an issue on GitHub
- Contact the team through the repository
Built with ❤️ for accessibility and inclusion by Team Equirk