LINK. is a full-stack customer intelligence web platform designed to help telecom operators take action on behavioral insights, predict customer dissatisfaction, and improve retention. This project was developed during Huawei x Kuwait University Internship Program Summer 2025 and is inspired by Huawei's SmartCare solution.

• Supervisor Trainee: Dr. Essam Alruqobah
• Supervisor Engineer: Eng. Ali Alsairafi
• Supervisor Huawei Site: Eng. Rahaf Alhasan

LINK. is built to interface with a Python-based churn prediction model trained on IBM’s public Telco Customer Churn dataset. The model uses classification techniques (Logistic Regression, XGBoost) with telecom-inspired feature engineering:

• Custom Metrics:

  • KQI: Key Quality Indicators
  • SQM: Service Quality Metrics
  • NPM: Network Performance Metrics

• ML Stack:

  • scikit-learn, XGBoost, Optuna (hyperparameter tuning)
  • Performance metrics: Accuracy, Recall, F1-score

ML Repo: View Machine Learning Model on GitHub

The LINK. platform integrates with a dedicated Flask microservice that delivers real-time churn prediction results. It acts as a bridge between the frontend and the trained machine learning model—analyzing customer feature data and returning churn probability scores for both single and batch requests.

• Built with Flask, scikit-learn, and XGBoost
• Receives API requests from the Node.js backend
• Supports batch prediction through .csv file uploads
• Powers the Predictions Page for interactive chart rendering

FLASK Repo: View Microservice on GitHub