Supply chain late delivery risk classifier · No leakage · No overfitting · LGB + XGB + CatBoost stacking · SHAP
LogisAI is an AI-powered Delivery Delay Prediction & Route Intelligence System that predicts delivery ETA, delay risk, and optimal dispatch windows using machine learning, traffic, weather, and route analytics. It features interactive maps, route optimization, analytics dashboards, and smart logistics insights through a modern full-stack interface.
Multi-class delivery risk prediction system using XGBoost, Random Forest, KNN and Logistic Regression on DataCo Supply Chain Dataset with real-time Gradio dashboard and agentic intervention system.
A responsive, card-based web interface for an AI-powered delivery prediction engine. Built with HTML, CSS, and jQuery, it allows users to input delivery factors—such as distance, traffic, and vehicle type—to receive real-time, API-driven estimates from a secure FastAPI backend hosted on Google Cloud Run. Includes 1-click random data generation.
Predicting Promised Delivery Time breaches in e-commerce supply chains using ML on the DataCo dataset.
Machine Learning project to predict food delivery time using features like traffic, weather, distance, and delivery partner details. Includes data analysis, feature engineering, and comparison of multiple regression models.
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