Introduction to Responsible Machine Learning
Educational framework for building interpretable, fair, and accountable ML systems.
Open-source course material teaching responsible ML principles including interpretability, fairness, and accountability. Designed for data scientists and ML engineers implementing governance practices. Combines theory with practical examples to embed compliance considerations directly into model development workflows.
Adjacent tooling.
AI Trust Services (KPMG)
KPMG's trusted AI framework for governance, risk, and compliance.
Aporia
Monitor, test, and safeguard LLMs in production with observability and guardrails.
Lumenova AI
Enterprise platform automating AI governance, risk assessment, and fairness monitoring.
ModelOp
AI ethics platform for model monitoring, bias detection, and governance.
Robust Intelligence
AI security platform detecting adversarial vulnerabilities and model failures.
Sardine
AI risk management for fraud detection with governance oversight.