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PROJECT / 05AI control plane

Kontrolr

Where should policy, tools, permissions, memory, and model routing live?

A privacy-conscious control plane for governing how people and agents use models, context, tools, and organizational authority.

Why this project exists

AI capabilities should be governed from a coherent control layer where policy, identity, tools, context, models, audit, and organizational authority can be reasoned about together.

The work, in sequence

Sample chronology from the prototype, awaiting editorial verification.

01
Evaluation

The harness joins the trust boundary

Sandboxing, recovery, tool semantics, and state handling are treated as part of the governed system.

02
Architecture

The control plane takes shape

Policy, routing, context, and audit are separated from individual AI applications.

Ideas leaving the laboratory

Longer arguments and field notes produced by the work.

One governed capability path

Every request crosses the same authority boundary before models, tools, or retained context become available.

Mermaid diagram

Rendering diagram. The source is available below.

Diagram source
flowchart TD
  accTitle: One governed capability path
  accDescr: Every request crosses the same authority boundary before models, tools, or retained context become available.
  n0["Identity + intent: Who is asking and what they need"]
  n1["Policy decision: Permissions, purpose, and risk"]
  n2["Capability route: Model, tool, and context selection"]
  n3["Audit record: Decision, execution, and recovery evidence"]
  n0 --> n1
  n1 --> n2
  n2 --> n3

No project lives alone.

This dossier remains focused on Kontrolr. Its dependencies and effects continue through the wider Factor-E constellation.

Next question

Can one policy model remain understandable while governing humans, agents, models, tools, and retained context together?

Return to the constellation