AI Control Plane — Review and Accelerator
Your AI acted. Who authorised it?
AI access is being solved. Authority is not.
AI agents can read your repositories, query business data and invoke internal tools.
Your logs may show what happened. They may not show why it was allowed. And an action can be permitted without ever being intended.
Can your organisation prove who authorised the action, which policy was enforced and what actually happened?
The Executive Proof Test
Could you prove this tomorrow?
Your approved coding agent reads a hidden instruction in a repository.
It then calls an internal tool using permissions your organisation granted.
The call succeeds.
Was that action intended? Can your teams demonstrate why it was permitted?
Identity
Who initiated the action, and on whose authority?
Scope
What operation was requested, against which resource?
Policy
Which rule was evaluated and enforced before execution?
Execution
Which model or tool ran, and what outcome was observed?
Evidence
Can your organisation reconstruct the decision and execution from independently controlled records?
Permission is not the same as authority. If your teams cannot answer these questions for one real AI execution path, establish the facts before expanding AI authority.
What the test can and cannot establish
The scenario shows how untrusted instructions can steer an agent that holds legitimate permissions. No policy engine or log can read an agent’s intentions. What your teams can establish is the gap between four different things:
- Declared permissions
- what the agent and its credentials could do
- Enforceable policy
- what was checked and enforced before the action ran
- Intended purpose
- what the person or team actually asked for
- Observed behaviour
- what ran, and with what outcome
The governance gap
Controls exist. Is there a chain of authority?
The question isn’t whether these controls exist. It’s whether they establish one enforceable, verifiable chain of authority.
- Identity and access management
- May authenticate people, services and agents without preserving who acted for whom as a request passes from a person to an agent to a tool.
- Model gateways
- May govern requests to models without controlling the tool actions an agent takes next.
- Provider logs
- May document individual events at one supplier without establishing the organisation’s own complete, independent evidence chain.
- Governance policies
- May exist without evidence that the correct policy decision was enforced on a particular action.
Not every platform has these gaps. Some products integrate identity, policy and evidence well, and the Review starts by establishing which of your controls already work. The governance question is the authority and evidence behind each individual action, not only which models are approved for use.
Why now
Before you approve the next AI rollout
Before increasing an agent’s authority, can you demonstrate the limits of its existing authority?
These are decisions a Head of Platform, CISO or CTO is asked to approve. Each is a natural point to establish the facts first:
- An AI agent is being granted access to internal systems.
- MCP tools are being connected to sensitive resources.
- A team is moving from read-only operations to actions that can change things.
- An AI application is moving into production.
- Security is investigating questionable AI activity.
- Audit or Risk is asking for evidence of individual AI decisions.
- More model providers or agent frameworks are entering the estate.
If AI use is limited to one provider’s chat product, with no tool access and little sensitive data, extending the controls you already run is often enough.
AI Control Plane Review · Two weeks · Standalone, paid
Know where your AI authority breaks down — and what to fix first.
In two weeks, we assess one real AI execution path, including identity propagation, model and tool access, policy enforcement and audit evidence.
We establish what already works, identify material control gaps and give Platform, Security and Risk a defensible basis for deciding what happens next.
What you receive
Current-state execution and trust-boundary map
The people, agents, models, gateways and MCP tools on the path, the routes between them, and where organisational control currently begins and ends.
Prioritised control-gap assessment
What already works, and where identity propagation, model and tool access, policy enforcement and audit evidence fall short, ranked by consequence.
Recommended target architecture
Where organisational control should sit and how requests would pass through it, with model providers remaining replaceable behind it.
First governed execution-path proposal
The one path to bring under control first, and the reasons for choosing it.
Practical remediation and implementation backlog
The work needed, in an order your teams can act on, and a proposed Accelerator scope should you want Parakletos to implement it.
The Review produces findings, a recommended architecture and a plan. It does not build or deploy a control plane; implementation is the separate, optional Accelerator. The deliverables cover the scope agreed before the Review starts, and the Review is not a comprehensive enterprise audit, a certification or a legal compliance assessment.
What you can do with them
- Brief your executive, risk or audit committee on where AI authority is, and is not, under organisational control.
- Implement the backlog with your own platform and security teams.
- Decide where a lighter approach is proportionate, so effort goes to the paths that hold the most authority.
- Scope and commission an implementation, with Parakletos or otherwise.
The Review stands on its own. Continuing into the Accelerator is optional.
Why Parakletos
Built, not just theorised.
Governator Pro — AI Control Plane
Parakletos’s own product · MVP available now
Governator Pro is Parakletos’s AI Control Plane product, and its MVP is available now. It covers identity, explicit policy decisions, governed model execution and audit evidence held in the organisation’s own database, separately from provider logs. Governed execution of MCP tool calls is in development.
The Review does not require Governator Pro. It assesses your estate and the controls you already have, and recommends a proportionate architecture.
What is implemented todayJason Southgate, founder
Professional background
Jason has almost 30 years’ experience, most of it before founding Parakletos, designing and building production systems for banking, retail, automotive and other regulated industries, mostly in cloud and platform engineering, with recent years concentrated on making AI systems reliable. He has completed a University of Cambridge programme in data science, machine learning and AI. Parakletos works directly with a small number of clients at a time.
About JasonA published framework you can assess first
White paper published by Parakletos AI Limited
The Governance Gap in Enterprise AI sets out the approach the Review applies: a nine-domain control framework, a minimum viable control plane for one path, five candidate first paths and an eleven-question readiness check. It is candid that Parakletos has a commercial interest in the answer, and covers when a control plane is the wrong answer.
Download the white paper (PDF, 30 pages)Optional · Six to eight weeks
AI Control Plane Accelerator
Implements the agreed first governed path, working with your platform and security teams. Scope, systems and integrations are agreed before work starts.
Continuing into the Accelerator is optional, and the Review’s recommendations do not depend on it. If you choose it, it starts from the Review’s backlog and proposed scope rather than a fresh discovery phase.
What the Accelerator delivers
Confirm the estate map and trust boundary
Building on the Review’s current-state map and proposed boundary, agree which requests must pass through organisational control and how bypass is prevented or detected.
Implement the first governed path
The agreed path, such as a coding assistant or a read-only MCP integration, routed through an organisation-controlled endpoint, including a deny path that shows a refused request was not forwarded.
Connect identity, policy enforcement and audit evidence
The path connected to your identity provider, requests evaluated against versioned policy, and an evidence record written for each material action.
Reference architecture as built
The path as implemented, the decisions taken and the reasoning behind them, and how further paths, providers and tools can be added.
Documentation and handover
A handover to the teams who will operate and extend the path, with the documentation they need to do so.
Whether it takes six weeks or eight depends on the path chosen and on the integration work your identity, network and logging platforms require. Neither engagement certifies compliance or removes AI risk.
Technical detail
Definitions and current capability
Where authority goes missing
- Unclear authority
- Nobody can say with confidence who, or what, was allowed to take a given AI action, on whose behalf and with which data.
- Fragmented access
- Models and tools are reached through personal keys, provider consoles, gateways and individually configured MCP servers, each with its own credentials and logs.
- Inconsistent policy
- The same request can be allowed on one route, blocked on another and never evaluated at all on a third.
- Inadequate evidence
- When security, audit or an incident review asks what happened, the answer has to be reconstructed from supplier dashboards and partial logs.
The outcome to aim for
A governed path that your organisation controls. Requests to models and MCP tools pass through an organisation-owned layer that identifies who is asking, evaluates policy, applies constraints and records evidence. Model providers sit behind that layer and remain replaceable: applications ask for an approved capability rather than a hard-coded provider, so a provider can be added or changed without changing how access is authorised and recorded.
Governator Pro: what the MVP includes today
The MVP is available now and includes OpenID Connect identity for end users, policy decisions recorded as evidence, model routing through a registry so providers stay replaceable, and metadata-only evidence tables that reject edits and deletions. That protection stops recorded history being rewritten, but it does not stop a compromised service adding false records, and the evidence is not signed or hash-chained, so it is not tamper-proof. MCP tool requests are evaluated against policy; governed execution of MCP tool calls is in development. No record, however well kept, shows what an agent intended; it shows what was permitted, decided and done.
Next step
Start with a 20-minute call
Book a 20-minute call with Jason Southgate and bring one AI path you are concerned about, or your teams’ answers to the five questions.
We will talk through what is in place today, whether a Review would be useful and what scope would make sense. If a Review is a good fit, we follow up with a proposed scope for you to agree before any work starts. If it is not, we will say so.
Book a 20-minute AI Governance CallOr email jason@parakletos.co.uk.
To share with colleagues, download the Executive Brief (PDF, one page). For the full framework, including the eleven-question readiness check on page 28, download the white paper (PDF, 30 pages).
