Supply Chain Risk Engine

Enterprise-Grade Risk Intelligence at Global Scale

Author: Ali-datasmith | Contact: rjptmhmmd@gmail.com

Executive Summary

Supply Chain Risk Engine is a production-ready platform that processes 1.5M+ global trade records to surface bottlenecks, geopolitical exposure, and financial risk — on zero-cost infrastructure.

Tech Stack

• Polars — Rust-backed dataframe engine, 3–5× faster than Pandas
• DuckDB — In-process OLAP SQL on raw Parquet, no server required
• Streamlit — Interactive dashboard, free cloud hosting
• NumPy — Vectorized composite risk scoring

Engineering Highlights

1.5M Rows on Free Tiers

• Polars chunked generation (300K rows × 5) keeps peak RAM under 400 MB
• DuckDB parquet_scan() runs GROUP BY aggregations without loading data into RAM
• Full risk aggregation completes in under 8 seconds on Colab free CPU

Composite Risk Model

Signal	Weight
Port Congestion	35%
Origin Geopolitical Risk	30%
Destination Risk	20%
Delay Ratio	10%
Disruption Noise	5%

How to Run

# Install
pip install polars duckdb numpy rich

# Run
python engine.py

Module Roadmap

Module	Status	Description
Module 1	✅ Complete	Data generation, DuckDB risk scoring
Module 2	🔄 In Progress	Streamlit dashboard
Module 3	📋 Planned	Live API ingestion
Module 4	📋 Planned	ML anomaly detection

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Built with precision. Engineered for scale. Deployed for free.