Documentation Hub
Welcome to the official documentation for the FairnessAudit platform. Learn how to ingest datasets, analyze model fairness, and deploy ethical AI systems.
Evaluation Metrics
Understand Demographic Parity, Equalized Odds, and other mathematical definitions of fairness.
Bias Mitigation
Learn about our state-of-the-art algorithms like Correlation Remover and Threshold Optimizer.
Getting Started
The FairnessAudit platform provides an enterprise-grade suite of tools for ML engineers and compliance officers. It allows you to test your machine learning pipelines against leading ethical frameworks seamlessly.
Core Infrastructure
- 1.Data Ingestion Engine: Safely process datasets with our secure, GDPR-compliant parsing layer.
- 2.Fairness Computation: Accelerated Python microservices computing Fairlearn metrics in real-time.
- 3.SHAP Tracing: In-depth feature importance and tree explainer visualizations.
Compliance & Certifications
All reports generated by the FairnessAudit platform conform to standard industry regulations including:
EU AI ACT
NIST AI RMF
IEEE 7003