NIST AI RMF Cookbook: Operational Templates and Schemas for AI Governance Implementation

The NIST AI RMF Cookbook provides practical, framework-aligned infrastructure for implementing the NIST AI Risk Management Framework (AI RMF 1.0). While the AI RMF establishes what organizations should consider when managing AI risks, this resource addresses how to operationalize those principles through ready-to-use policy templates, structured documentation schemas, and regulatory crosswalks. This release (v0.2.1) includes: 146 model cards covering major AI providers (Anthropic, OpenAI, Google, Meta, Mistral, Cohere, xAI, Amazon, Microsoft, DeepSeek, and others) with standardized risk assessments and control mappings Multi-framework alignment integrating CIS Controls v8.1, CIS-RAM (Risk Assessment Method), and Colorado SB24-205 requirements alongside NIST AI RMF Comprehensive governance framework with policies, technical standards, and risk scenario library YAML validation schemas for model cards, data cards, risk assessments, control mappings, and evaluation plans Proxmox astronomy cluster implementation demonstrating practical application with deployment-specific policies and evidence Framework crosswalks mapping NIST AI RMF to CIS Controls v8.1, CIS-RAM, and Colorado SB24-205 Implementation guidance for GRC teams, ML engineers, and compliance officers Problem addressed: Organizations face increasing pressure to demonstrate AI governance maturity, but few free, production-ready resources exist to bridge the gap between abstract frameworks and operational compliance. This cookbook synthesizes AI governance best practices into reusable artifacts designed for organizational adoption. Intended audience: Governance, Risk, and Compliance (GRC) professionals, AI/ML engineering teams, information security officers, and policy teams building or maturing AI risk management programs. What's new in v0.2: Expanded from 42 to 146 model cards, added multi-framework compliance mappings (CIS Controls v8.1, CIS-RAM, Colorado SB24-205), comprehensive policy and standards library, validation schemas, and organization-specific implementation examples. Repository structure consolidated for better navigation and usability.