The Articsledge AI Lead Scoring System is a production-ready application kit that helps sales teams prioritize leads using machine learning. You receive a complete, fully-coded solution including a trained Gradient Boosting model with 83.3% accuracy, React frontend with TypeScript, FastAPI backend, and Docker deployment configuration.
The system analyzes leads across multiple dimensions including engagement metrics, firmographic data, demographic information, and behavioral patterns to generate scores from 0 to 100. Leads are automatically categorized as Hot (70-100), Warm (40-69), or Cold (0-39) to help your sales team focus on the most promising opportunities. The application includes a visual dashboard with analytics, bulk CSV import capability, individual lead management, and a full RESTful API with interactive Swagger documentation.
Your purchase includes all source code for both frontend and backend, a pre-trained machine learning model achieving 83.3% accuracy with 86.7% F1-score and 0.913 ROC-AUC on test data, 1,200 synthetic training records for model development, complete Docker and Docker Compose configuration files, SQLite database setup with SQLAlchemy ORM, and comprehensive documentation covering installation, usage, API endpoints, and troubleshooting.
The frontend is built with React 18 and TypeScript, styled with Tailwind CSS, and includes data visualization using Recharts. The backend uses Python 3.11+ with FastAPI framework, Pydantic for validation, and scikit-learn for machine learning. The entire stack is containerized with Docker for straightforward deployment on Windows, macOS, or Linux systems with minimum 4GB RAM and 2GB disk space.
IMPORTANT NOTE: This application has been fully developed with all features implemented. However, it has not been tested in a live production environment. You should expect to perform integration testing and may encounter minor bugs that require fixing. Basic technical knowledge and development skills are required. You will need Docker Desktop installed and should allocate 1-2 hours for final testing and debugging before deploying to production.
You can modify the application for your business needs, build new products on top of it, and operate it as a commercial SaaS service. You may not open-source, resell, redistribute, or use it to create competing lead scoring products.
NO REFUNDS: Due to the digital nature, all sales are final.