AI-assisted supply-chain risk scoring toolkit for suppliers, ESG, resilience, and predictive sourcing.
Project description
SupplyRisk AI
AI-assisted supply-chain risk scoring for predictive sourcing, ESG, resilience, and supplier strategy.
SupplyRisk AI is an open-source, production-ready Python library designed to help organizations evaluate, monitor, and manage supplier risk using a structured, AI-assisted scoring model.
It enables procurement, sourcing, and supply chain teams to make data-driven decisions by combining multiple risk dimensions into a unified risk score.
Overview
Modern supply chains face increasing complexity due to:
Global supplier dependencies
Geopolitical and country-level risks
Financial instability of vendors
Delivery and operational disruptions
ESG (Environmental, Social, Governance) compliance requirements
Cybersecurity exposure across third-party vendors
SupplyRisk AI provides a lightweight and extensible risk engine to quantify these risks and support predictive sourcing and resilient supply chain design.
Key Use Cases
Supplier risk scoring and ranking
Procurement decision support
Predictive sourcing strategies
ESG-aware supplier selection
Third-party risk management (TPRM)
Supply chain resilience planning
Vendor onboarding and evaluation
Features
Multi-dimensional supplier risk scoring
Country, financial, delivery, ESG, and cyber risk modeling
Simple and extensible scoring framework
Lightweight and fast execution
CLI + Python SDK support
Ready for integration into ERP / SAP / Ariba workflows
Core capabilities
Supplier Risk Scoring: Generate a composite risk score based on multiple weighted factors
Predictive Sourcing: Identify high-risk suppliers early and support better sourcing decisions
ESG Risk Evaluation: Incorporate sustainability and governance factors into supplier selection
Cyber Risk Awareness: Assess third-party cyber exposure risks
Supply Chain Resilience: Improve decision-making under uncertainty and disruption scenarios
Integration Ready: Can be embedded into procurement analytics pipelines and enterprise systems
Install
pip install supplyrisk-ai
Python Usage
from supplyrisk_ai.core import SupplierRiskInput, score_supplier_risk
items = [
SupplierRiskInput(
supplier="SupplierA",
country_risk=20,
financial_risk=40,
delivery_risk=30,
esg_risk=10,
cyber_risk=50
)
]
scores = score_supplier_risk(items)
for s in scores:
print(f"{s.supplier}: Risk Score = {s.total_score}")
CLI Usage
supplyrisk score supplier_risk.csv
CSV columns: supplier,country_risk,financial_risk,delivery_risk,esg_risk,cyber_risk
Build and Publish
python -m pip install --upgrade build twine
python -m build
twine check dist/*
twine upload dist/*
MIT License
Author: Jagadeesh Vasanthada
Project details
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