Implementation Guide

Deploying RMACD in Your Enterprise

View on GitHub Last synced: 2026-03-01 04:08 UTC

Implementation Guide

This guide provides step-by-step instructions for implementing the RMACD Framework in your organization.

Prerequisites

Before implementing RMACD, ensure you have:

  1. Inventory of AI agents — Document all deployed or planned autonomous agents
  2. Identified stakeholders — Change management, security, compliance teams
  3. Approval workflow infrastructure — Ticketing system, notification capabilities

Step 1: Choose Your Implementation Model

Two-Dimensional Model (RMACD + HITL)

Choose this if: - Your organization does not have formal data classification - You need rapid adoption - You're piloting with a limited scope

Three-Dimensional Model (RMACD + HITL + Data Classification)

Choose this if: - You have an established data classification scheme - You operate in a regulated industry - Your agents access data across multiple sensitivity levels

Step 2: Define Permission Profiles

Start with the provided templates:

  • Observer — Read-only agents
  • Logistics — Read + Move agents
  • Provisioning — Read + Move + Add agents
  • Operations — Read + Move + Add + Change agents
  • Administrator — Full RMACD (with restrictions on Restricted data)

Customize as needed for your agent types.

Step 3: Configure Policy Enforcement

Integrate RMACD with your agent runtime:

  1. Load permission profiles from your policy store
  2. Intercept agent operation requests
  3. Evaluate against the governance matrix
  4. Enforce autonomy requirements (allow, notify, queue for approval, deny)
  5. Log all decisions for audit

Step 4: Integrate Approval Workflows

Map autonomy levels to your existing systems:

Autonomy Level Integration
Autonomous No integration needed
Logged Enhanced logging pipeline
Notification Email, Slack, Teams alerts
Approval ServiceNow, Jira, custom ticketing
Elevated Approval CAB workflow, senior management queue
Prohibited Block with explanation

Step 5: Test and Validate

Before production enforcement:

  1. Run in audit-only mode (log decisions, don't enforce)
  2. Review logs for unexpected denials or approvals
  3. Adjust profiles and matrix as needed
  4. Gradually enable enforcement

Step 6: Monitor and Iterate

Ongoing operations:

  1. Review agent behavior patterns
  2. Adjust permissions based on demonstrated trustworthiness
  3. Respond to incidents and update profiles
  4. Conduct periodic compliance audits

Python Tools Registry

A reference Python implementation is available in the tools-registry/ directory:

tools-registry/
├── rmacd_tools_registry.py       # Core implementation (750+ lines)
├── example_usage.py              # Usage examples with 27 pre-configured tools
├── test_registry.py              # Test suite (43 tests)
├── mcp_integration.py            # MCP auto-classification bridge
├── rmacd_tools_catalog.json      # Pre-configured tool catalog
├── rmacd_permission_profiles.json # Standard permission profiles
└── README.md                     # Detailed documentation

Key features: - Tool registration with RMACD classification - Permission validation against agent profiles - Risk scoring for tools and workflows - Audit logging for compliance - MCP tool auto-classification

See tools-registry/README.md for detailed usage instructions.


Platform-Specific Guides

Coming soon:

  • Kubernetes / Container orchestration
  • AWS / Azure / GCP agent integration
  • LangChain / AutoGPT integration
  • ServiceNow integration

Need Help?

Ready to get started?

Create your first RMACD agent profile or review the full framework specification for complete governance details.