Understanding AI Governance

How AgentAnchor Works

A complete guide to AI agent governance—from basic concepts to advanced implementation. No prior knowledge required.

What is AI Governance?

AI Governance is the system of rules, checks, and balances that controls what AI agents can do. Think of it like the management structure for AI employees.

Without Governance
  • • AI makes decisions with no oversight
  • • No way to prove what AI did or why
  • • Compliance violations go undetected
  • • Rogue agents can cause damage
  • • No accountability for AI actions
With AgentAnchor
  • • Every action is checked and logged
  • • Complete audit trail for compliance
  • • Trust-based access control
  • • Instant emergency shutoff capability
  • • Clear accountability chain

Real-World Analogy: The New Employee

Imagine hiring a new employee. You wouldn't give them access to all company systems on day one. They start with limited access, prove themselves over time, and gradually earn more responsibility.

AgentAnchor does the same for AI agents. New agents start in a "sandbox" with minimal permissions. As they demonstrate reliable behavior, they earn higher trust levels and unlock more capabilities. Make a mistake? Trust drops and permissions are revoked.

Trust Scores Explained

Every AI agent has a Trust Score from 0 to 1000. This score determines what the agent can do—higher scores unlock more capabilities.

The 6 Trust Tiers

T5
900-1000
Certified

Full autonomy. Can perform any action without human approval. Reserved for thoroughly audited, long-running agents.

T4
700-899
Verified

High trust. Can handle sensitive operations. Minimal oversight required.

T3
500-699
Trusted

Extended capabilities. Can perform most standard operations independently.

T2
300-499
Established

Proven reliability. Basic operations approved, complex ones need review.

T1
100-299
Provisional

Learning phase. Limited actions, frequent human checkpoints.

T0
0-99
Sandbox

New or untrusted. Read-only access, all actions require approval.

Trust Increases When...
  • ✓ Tasks completed successfully
  • ✓ Consistent uptime and reliability
  • ✓ Compliance checks passed
  • ✓ Security audits cleared
  • ✓ Positive human feedback
Trust Decreases When...
  • ✗ Tasks fail or produce errors
  • ✗ Security violations detected
  • ✗ Policy breaches occur
  • ✗ Extended periods of inactivity
  • ✗ Anomalous behavior flagged

Capability Gating

Capability Gating is like a bouncer at a club. Before any action is taken, the system checks if the agent has enough trust for that specific action.

Every Action Goes Through This Check

Agent requests action

Trust vs. Risk checked

ALLOW
DENY
ESCALATE
DEGRADE

Decision made

ALLOW

Trust is sufficient. Action proceeds immediately.

DENY

Trust is too low. Action blocked completely.

ESCALATE

Borderline case. Sent to human for approval.

DEGRADE

Allowed with reduced scope or added restrictions.

Risk × Trust Matrix

The decision isn't just about trust—it also considers how risky the action is. High-risk actions need higher trust. Low-risk actions can proceed with lower trust.

Trust LevelLow RiskMedium RiskHigh RiskCritical Risk
T5 Certified
T4 Verified
T3 Trusted
T2 Established
T1 Provisional
T0 Sandbox
Auto-approved
Needs review
Denied

Circuit Breakers & Safety

Sometimes you need to stop an AI agent immediately. Circuit breakers provide instant control.

Pause

Temporarily halt an agent's actions. Agent can resume when you're ready.

Restrict

Reduce an agent's trust level immediately. Capabilities automatically limited.

Kill Switch

Complete shutdown. Revokes all permissions and halts all activity instantly.

Getting Started

For Enterprises

Get a demo of AgentAnchor configured for your use case. See how governance integrates with your existing AI infrastructure.

Request Demo

For Developers

Install the CAR client (TypeScript contracts for the BASIS standard) and start building governed agents. Full TypeScript support with comprehensive documentation.

npm install @vorionsys/car-client
View Documentation