aribaiq 0.1.0

AI-powered procurement and sourcing analytics toolkit inspired by modern Ariba-style workflows.

aribaiq

aribaiq is an open-source Python library for AI-powered procurement, sourcing, and supplier intelligence analytics.

It is designed to help teams turn raw sourcing or ERP-exported data into practical insights through:

• supplier intelligence scoring
• spend visibility and optimization signals
• ESG-aware evaluation
• responsible AI checks
• AI-ready prompt generation for copilots and LLM workflows

The package is lightweight, vendor-neutral, and suitable for analytics teams, engineers, procurement strategists, and open-source developers building modern source-to-pay intelligence solutions.

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Why aribaiq?

Procurement teams often have large datasets but limited decision visibility.

Common challenges include:

• inconsistent supplier performance evaluation
• difficulty identifying concentration risk
• scattered ESG and compliance indicators
• limited explainability in AI-assisted sourcing decisions
• manual effort in turning analytics into executive summaries

aribaiq helps solve these problems with transparent analytics, governance-aware checks, and AI-ready outputs.

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Core Features

Supplier intelligence scoring

Ranks suppliers using business-relevant signals such as:

• on-time rate
• defect rate
• ESG score
• spend concentration

Spend analytics

Highlights:

• category concentration
• supplier spread
• consolidation opportunities
• single-supplier exposure

ESG scoring

Provides weighted ESG evaluation support for suppliers.

Responsible AI checks

Includes:

• missingness checks
• invalid value detection
• representation imbalance warnings

GenAI-ready prompts

Builds provider-agnostic prompts for:

• internal copilots
• chat assistants
• LLM-based reporting pipelines

CLI included

Run analytics directly on CSV, JSON, or JSONL files.

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Installation

pip install aribaiq


## Author
Jagadeesh Vasanthada

## LICENSE

MIT License

Copyright (c) 2026

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