Control Plane Convergence | Unifying Identity, Action and Assurance Across Enterprise AI | R.A.H.S.I. Framework™
An agent is approved after an administrator reviews its owner, data and tools. Months later, its sponsor changes.
Does its access still serve an authorized purpose, and can the enterprise establish that from the resulting events?
Microsoft describes Agent 365 as a control plane for observing, securing and governing agents.
Entra addresses AI identity and access.
Agent inventory and Agent ID serve different scopes. Each contributes controls; their coexistence does not guarantee a coherent account of authority.
A control plane is not a dashboard.
It is the architecture through which authority becomes governable.
Identity and knowledge
- Which human, application or agent identity acts, under whose sponsorship?
- Does permitted retrieval still fit the approved purpose?
- Source provenance and version history cannot be assumed to exist everywhere.
Model and tool
- Is the model appropriate for the work, region and risk?
- Which connectors, APIs, skills, plugins, MCP servers or other agents can it invoke?
- Tool reach can change the consequence of an otherwise unchanged agent.
Action and policy
- Is the agent reading or writing, acting internally or externally, taking a reversible step or a consequential one?
- A policy needs an applicable decision point and effective enforcement.
- Higher-impact actions merit stronger authorization and oversight.
Evidence, risk and human authority
- Can identity, policy decisions, tool calls, outcomes, exceptions and approvals be related to the same event?
- Does review account for autonomy, privilege, sensitive data and blast radius?
- Who remains accountable when roles change?
A control surface configures or exposes a capability. A control decision determines what.
| R.A.H.S.I. Framework™
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Control Plane Convergence | Unifying Identity, Action and Assurance Across Enterprise AI | R.A.H.S.I. Framework™
Control Plane Convergence connects agent identity, tool reach, runtime policy, evidence and human accountability into a governable enterprise AI architecture.
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