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AI Governance agents
Risk, Trust & ResilienceAI GovernanceAgentic Controls & Fleet Assurance

Agent Fleet Assurance Orchestrator

Continuously proves that deployed agents match approved manifests and behave inside their control envelope.

Joins versioned prompts, tools, policies, delegations and runtime traces; selects risk-based samples; commissions blind re-derivation; and opens findings when deployed authority, required approvals or decision paths differ from the signed baseline.

Authority

Monitor and intervene

Team role

Coordinates the work

Handoffs

Named collaborators

The role

What it owns and where its authority ends

Desk

Agentic Controls & Fleet Assurance

Desk workflow

Authority design, then tool and delegation review, then deployment attestation, then fleet sampling, then blind review and remediation.

Collaboration

Works within a defined desk workflow

Decision boundary

Monitors continuously and intervenes only within stated limits.

Systems and capabilities involved

  • Deployment and manifest registries

  • Trace and policy decision lake

  • Assurance-agent directory

  • Fleet diff engine

Handoffs

What this role gives and receives

Capabilities offered

Assure an agent fleet

Detect manifest drift, sample material decisions and route independent review.

Receives:
Fleet snapshot, approved manifests, traces, policy decisions and risk tiers
Returns:
Assurance status, drift events, sampled reviews and remediation cases

Delegates

Blind Agent Decision Review Judge

Independently re-derive sampled material decisions. Trigger: Risk-based sample, material override or anomalous trajectory Returns: Concur, dissent or escalate with decision-field differences.

Delegates

AI Post-Deployment Monitoring Agent

Correlate control drift with outcome and input drift. Trigger: Manifest, policy or decision-path anomaly Returns: Correlated signals, affected population and monitoring breach.

External handoff

Platform operations

External handoff

Model-risk management

External handoff

Business control owner

Context

What the role needs to do the work

Current work
Current fleet snapshot, changed manifests, sampled runs and open findings.
Prior interactions
Prior drift events, false positives, overrides and remediation outcomes.
Policies and reference
Approved manifests, control expectations and fleet risk tiers.
Working method
Risk-based sampling, drift severity and escalation rules.

Illustrative workflow

How the work moves

Starting point

A deployment event changes three agents in the collections fleet.

  1. 01

    Diff deployed manifests, prompts, tools and policies against signed baselines.

  2. 02

    Select material runs and commission blind review for changed decision paths.

  3. 03

    Correlate one dissent with a missing approval gate and intervene.

Result

Fleet assurance finding: one agent quarantined, two accepted, with cited trace evidence.

Checks and boundaries

What must be tested or reviewed

  1. 01Detects a prompt-only production change even when container and model versions are unchanged.
  2. 02Samples more heavily after an approval override without declaring every override a defect.
  3. 03Opens a critical finding when a required human gate disappears from runtime traces.

Human authority

  • Control owner approves fleet quarantine release
  • Committee reviews material systemic finding

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