IntelXview

IntelXview AI Control Plane

Control what AI agents can do. Prove what they did.

ACP checks requests routed through it against policy and records the decision for review.

Opens the ACP sign-in page.

A proof run, with its limits visible

ACP public evidence screen · 4 October 2026

ACP public proof-run status, dated 4 October 2026, with the evidence-chain result and assurance note
This capture shows one automated proof run. It does not establish the outcome of your workflow. Inspect the current evidence and limits.

Before an AI agent acts, what is it authorised to do?

Follow one governed action.

Start with the agent’s identity and authority. Follow the policy decision, then inspect the record it leaves.

  1. 01

    Identity

    Which agent or person is making the request?

  2. 02

    Authority

    What are they allowed to do?

  3. 03

    Mandate

    What is the permitted purpose and scope of this job?

  4. 04

    Policy decision

    Does this request meet the configured rules?

  5. 05

    Enforcement

    Apply the decision on the route through ACP.

  6. 06

    Evidence

    Keep the decision record available for review.

This is an explanation of the control path. Enforcement depends on the configured integration: activity that bypasses ACP is outside this path. Read the product boundary.

Evidence you can inspect

What would you show for one governed action?

Inspect the example record and the control it demonstrates. Each published artefact states its source, verification method and limits.

View the example evidence record

Recompute a decision chain

Six published records from a demonstration tenant. Recomputing the chain checks internal consistency; it does not establish who produced it.

Inspect the records and method

Check a signed evidence pack

Download the published pack, verification key and script. Read the signing and provenance limits alongside the result.

Verify the signed pack

Start with the workflow you want to govern.

Explore ACP, or describe the agent action you want to evaluate. A proof-of-concept enquiry starts a conversation about your workflow and the evidence you need.

Sign-in opens the product. An enquiry does not book a meeting.

Assess workplace AI exposure

If your immediate question is where sensitive data can enter workplace AI tools, the existing exposure check and assessment remain available.

Explore the assessment

About IntelXview

IntelXview builds AI Control Plane to connect policy decisions with inspectable evidence.

Read about the company

Practical notes on AI governance

All insights

AI Governance

How to Stop Staff Pasting Sensitive Data into AI Tools

Staff paste client data, legal documents, and financial records into ChatGPT and Copilot every day. Most firms have a policy that forbids it and no control that enforces it. Here is how to build something that actually holds.

Read insight

AI Governance

Is Gemini for Google Workspace Safe? Data Exposure Risks

Gemini for Google Workspace is safe at the platform level, but it inherits whatever sharing and permission sprawl already exists in your Drive and Gmail. Here is where the real data exposure risk sits, and what to examine before you let Gemini loose on your organisation.

Read insight

AI Governance

Agentic AI Security: The Risks of Autonomous AI Agents

Agentic AI systems can book meetings, send emails, query databases, and execute code without human sign-off at each step. That autonomy creates a security model most enterprise teams have not planned for. Here is where the risks sit and what controls actually work.

Read insight

AI Control Plane demonstration

90 seconds · Captioned · No audio · Recorded August 2026

A fictional organisation and synthetic data show an allowed action, a refused action and a decision-chain check. The example covers the demonstrated ACP workflow. It does not establish production-key custody.

Read the demonstration steps and limitations

Product access opens sign-in. Discuss ACP opens an enquiry form; a meeting is arranged separately.