- The Kalsnet (KNet) ASI Decision Intelligence Platform, developed by Randy Singh of Kalsnet (KNet) Consulting Group, is a single web application that shows how an advanced decision engine can turn business data into clear, explainable and financially justified actions. - It brings together six enterprise use cases in one workspace: Predictive Maintenance, Customer Churn Prediction, Credit Risk Scoring, Fraud and Anomaly Detection, Demand Forecasting and Inventory and Customer Segmentation. - It is built in Python with Streamlit for the interface, scikit learn for machine learning models such as Random Forest, Gradient Boosting, Logistic Regression, Isolation Forest and K Means, Plotly and Matplotlib for charts, Graphviz for workflow and decision diagrams, and FPDF for report generation. - Users can work with synthetic demonstration data or upload their own data, map their columns, tune the engine to their business costs, and download results as PDF, TXT and CSV reports. In the real world, it helps organizations reduce equipment downtime, retain profitable customers, lower credit losses, stop fraud early, keep the right stock levels and target marketing more effectively, with every recommendation backed by transparent formulas, key drivers and clear financial impact.
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