AI System Governance

Govern models, embeddings, RAG pipelines, and prompt libraries across your AI stack.

Overview

AI Governance extends data governance to cover the complete AI/ML lifecycle.

AI Assets

Models: ML models and LLMs with version tracking
Vector Stores: Embeddings and their source data
RAG Pipelines: Retrieval chains and their data sources
Prompts: Prompt templates and libraries

Model Registry

POST /api/v1/ai/models
{
  "name": "Customer Churn Model",
  "type": "classification",
  "version": "2.1.0",
  "training_data": ["table:customers", "table:orders"]
}

EU AI Act Compliance

Classify AI systems by risk level and generate required documentation.