AI Agent Control Plane Implementation Guide

Quickstart PoC path01

A Rutile PoC should prove four flows: register agents, route tool calls, broker temporary access, and produce audit evidence.

• Select one high-value agent workflow.
• Register the agent owner, tools, data scopes, and risk tier.
• Route MCP/API calls through Rutile policy evaluation.
• Review audit events with the security team.

agent:
  id: sample-procurement-agent
  owner: security-platform-team
  purpose: approved supplier risk review
  tools: [approved_crm.read, vendor_risk.query]
policy:
  default: deny
  allow_when: owner_verified && change_ticket_approved
  max_duration: 15m

Core concepts02

Rutile models an AI agent as a governed non-human identity with owner, purpose, authority, tool scope, risk tier, and lifecycle state.

Architecture overview03

Rutile is positioned between agent runtimes and enterprise tools so policy is evaluated before execution, not only after logging.

• Connect identity providers for owner and group context.
• Route LLM, MCP, A2A, SaaS, database, and cloud calls through the policy proxy.
• Stream decisions and outcomes to audit, SIEM, and reporting pipelines.

Agent registry data model04

The registry gives security teams a searchable inventory of every agent that can act on enterprise systems.

Policy model05

Policies combine identity, intent, tool, resource, data sensitivity, approval state, time, and runtime risk.

{
  "effect": "allow_with_jit",
  "when": {
    "agent.risk_tier": "medium",
    "tool": "vendor_risk.query",
    "data_scope": "approved_supplier_records",
    "approval": "change_ticket_approved"
  },
  "grant": { "duration": "15m", "access": "read_only" }
}

Integration guide06

Rutile is designed to coexist with IAM, PAM, SIEM, DLP, LLM gateways, MCP servers, A2A agents, and internal platform tooling.

• Use existing IAM as the source of truth for people, groups, and owners.
• Keep existing SIEM as the investigation surface while Rutile supplies agent-native events.
• Use Rutile policy proxy for enforcement on agent tool execution paths.

Audit log specification07

Audit events must explain who delegated work, what agent acted, what tool was used, what access was granted, and what happened.

Security model08

Rutile aligns with zero-trust principles: never trust an agent by default, always verify identity and context, and continuously monitor execution.

• Default deny for unknown agents and unknown tools.
• Short-lived credentials and explicit scopes for approved tasks.
• Policy enforcement before tool execution and runtime response after suspicious behavior.
• Human approval for high-risk actions and sensitive data scopes.

Compliance mapping09

Rutile evidence can support AI governance and security review programs by mapping agent controls to recognized frameworks.

Deployment options10

Deployment should match data sensitivity, regulatory requirements, and network architecture.