BoxAI Governance Control Plane · Generic Case StudyIBMLive · reference frameworkAI Governance Control Plane
From documented policy to provable control
A generic enterprise case study, a live reference framework, and a pitch for why ControlPlane was built this way. Documentation alone cannot prove control — only an enforced, observed, and evidenced pipeline can. This module walks the five governance domains, the end-to-end golden trace, and the program outputs that turn policy into regulatory proof.
Control Status Summary
11 of 14 controls enforced in-band
01 · Entry
Governance Maturity Model
Where the active client sits today, derived from the live simulation. The goal is Level 5 — continuous governance assurance.
02 · Architecture Vision
Business Policy → Regulatory Proof
A 7-layer pipeline from written policy to packaged regulatory proof, and the four enterprise outcomes it enables. Click any node for detail.
03 · Control Plane Domains
Five Domains of AI Governance
Identity & Lifecycle, Governance Gate, Telemetry & Evidence, Tools & MCP Access, and Audit & eDiscovery — each with its core principle and mechanism catalog (CP-01 through CP-14). Click a card to expand description, decision focus, example, and best practice.
Domain 1 · Identity & Lifecycle
Every agent has a verifiable identity, a declared owner, and a managed lifecycle from registration to retirement.
04 · Golden Trace Flow
An End-to-End Governed AI Action
Run the golden trace to watch a single action flow through identity, policy, tools, model, output, and evidence — each node proving what it must.
Golden Trace · End-to-End Governed Action
User → Identity → Agent → Policy → Tool → Model → Output → Outcome → Evidence
User
Identity & Authority
Approved Agent
Policy & AuthZ
Tool / Data
Model
Output Protection
Outcome
Evidence Repository
Golden Trace Log
IDLEPress Run Golden Trace to stream the governed action.
05 · Guided Workshop
Workshop Session Flow
Five sessions walked in sequence — the original workshop structure. Check off expected outcomes, review key decisions, and close each session.
Workshop Mode · Guided Session Flow
5 Sessions · in sequence
Objective
Establish that every agent has a verifiable identity, a declared owner, and a managed lifecycle.
Validation question
Can you list every production agent, its owner, and its current lifecycle state right now?
Expected outcomes
Key architecture decisions
- Adopt a single agent catalog as source of truth
- Bind identity to credentials that expire
- Make retirement a telemetry-emitting event
06 · Development Process
Governance Architecture Development Process
Seven steps to build the control plane, each producing a named output artifact — from the material AI action taxonomy to golden trace validation.
Governance Architecture Development Process · 7 Steps
Technical
Enumerate the actions the business treats as material (advisory, automated, customer-facing, PII-touching). Each gets a risk class and an owner.
Business
Focuses governance where it matters - not every API call is material, but the ones that touch customers or money are.
07 · Success Criteria
Program Outputs & Success Criteria
What a complete governance program produces: eight deliverables and a six-point success criteria strip — the proof the program is real.
08 · Traceability Model
From Requirement to Deliverable
The 8-layer traceability model: how an abstract governance requirement is realized, layer by layer, into a client deliverable and validation evidence.
Traceability Model · 8 Layers
How abstract governance requirements become implementable architecture and validation evidence. Each layer is the predecessor of the next — a requirement at the top is realized as a deliverable at the bottom.
| # | Layer | Telemetry & evidence focus |
|---|---|---|
| 1 | Enterprise Requirement | Why traceability is required |
| 2 | Platform Requirement | Correlation, identity, governance capabilities |
| 3 | Architecture Design | Trace propagation and event flow |
| 4 | Security Control | Policy enforcement and authorization |
| 5 | Platform Capability | Telemetry, evidence, and audit services |
| 6 | Implementation Component | Gateway, runtime, policy engine, identity, repository |
| 7 | Validation Evidence | Golden Trace, audit artifact, proof of enforcement |
| 8 | Client Deliverable | Standards, architecture, governance evidence model |
09 · Operating Model
Who Owns What
Governance never executes anything — the platform does. This matrix maps each responsibility area to the functional team that owns it, so every demand has an owner and an evidence path.
10 · Live Risk Playback
Risk Score Replay
Play back the simulation event stream and watch how the composite risk score moves across AI cost-attribution events — anomaly, policy gate, PII scan, prompt injection, and approval each contributing. Inject an anomaly or governance incident to see the score spike in real time.