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Deploy AI Agents Safely

A control plane that protects your apps and data while agents do the work.

AI Controller is a control plane that sits between your agents and the systems they act on. Instead of giving each agent its own credentials and direct access to your apps, you point them at the controller and choose exactly what each one is allowed to do. Every request goes to the controller first, which checks who is asking, confirms the action is allowed, runs it, and records what happened. So an agent never holds credentials or completes an action you would have refused, because you set the policy before anything runs. Built in Go for lightweight, fast performance.

Runs on Windows, Mac, Linux, and your own servers.

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The problem

AI becomes valuable when it can act. That is also when control matters most.

Everyone treats AI as a magical oracle on a mountaintop where you ask a question and it hands back the answer.

But answers are not the real opportunity. The real value comes when AI can use your systems, complete a workflow, and return finished work.

That requires access to email, files, databases, infrastructure, and business applications. Connecting an agent directly to all of it creates a new problem: credentials spread across tools, permissions become difficult to reason about, and important actions happen without one place to control or review them.

The answer is not to keep AI trapped in a chat window. The answer is to give it a controlled way to act.

The control layer

One place between every agent and every system.

AI Controller sits between the AI and the systems where work happens. Agents ask for a capability. AIC verifies the client, checks what it is allowed to use, executes through the correct plugin, and records the result.

The agent gets the outcome it needs. It does not get the underlying password, token, connection string, or unrestricted access to the system behind it.

Your agents can move faster because control, credentials, execution, and visibility live in one place.

How it works

A controlled path from request to result.

  1. Connect the agent

    Register OpenClaw, an MCP client, a custom agent, or a business application with its own identity.

  2. Add the capabilities

    Install and configure plugins for the tools, data, and infrastructure the agent needs to reach.

  3. Scope the access

    Choose which client can use which capabilities. Disable, revoke, or rotate access without reworking every agent.

  4. Run and observe

    AIC executes the request through the controlled connection and records the activity, outcome, and source.

What AIC controls

The access AI needs, with the boundaries you require.

Agent and client identity

Give every machine client its own identity, credentials, status, and access lifecycle.

Protected credentials

Keep connector secrets inside the controller. Agents receive authorized outcomes, not the credentials behind them.

Scoped capabilities

Grant only the tools each client needs, then enable, disable, rotate, or revoke access centrally.

Plugin based execution

Connect business systems through explicit capabilities instead of giving agents broad network or account access.

Operational visibility

See authentication activity, tool calls, process activity, completed work, denials, and operator changes in one console.

Multiple ways to connect

Use MCP for agent discovery and bounded tool calls, with secure APIs for applications and durable operational work.

Built for action

The agent decides what to do. AIC controls how it gets done.

OpenClaw, Claude, ChatGPT, Cursor, or your own application can reason about the work and request the next action. AI Controller owns the execution boundary: authentication, authorization, credentials, connectors, runtime controls, and records.

That separation lets you change agents and models without rebuilding every integration or distributing powerful credentials across every AI tool.

AI agents and applications

AI Controller Authenticate Authorize Execute Record

Your tools, data, and infrastructure

Give AI the ability to act. Keep control of what it can do.

Tell me what your agents need to reach and what must stay protected. I will show you how AI Controller can put a secure execution layer between them.

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Built for controlled access, protected credentials, and accountable execution.