Metadata-Version: 2.4
Name: supplyrisk-ai
Version: 0.1.2
Summary: AI-assisted supply-chain risk scoring toolkit for suppliers, ESG, resilience, and predictive sourcing.
Author: Jagadeesh Vasanthada
License: MIT
Project-URL: Homepage, https://github.com/raghavachellu/supplyrisk-ai
Project-URL: Repository, https://github.com/raghavachellu/supplyrisk-ai
Project-URL: Issues, https://github.com/raghavachellu/supplyrisk-ai/issues
Keywords: sap,ariba,erp,procurement,supply-chain,analytics,ai,automation,p2p
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: typer>=0.12.0
Requires-Dist: rich>=13.7.0
Provides-Extra: dev
Requires-Dist: pytest>=8.0.0; extra == "dev"
Requires-Dist: build>=1.2.0; extra == "dev"
Requires-Dist: twine>=5.0.0; extra == "dev"
Dynamic: license-file

# 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

```bash
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

```bash
supplyrisk score supplier_risk.csv
```

CSV columns: `supplier,country_risk,financial_risk,delivery_risk,esg_risk,cyber_risk`

## Build and Publish

```bash
python -m pip install --upgrade build twine
python -m build
twine check dist/*
twine upload dist/*
```

## MIT License

Author: Jagadeesh Vasanthada

