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Marshal AgentsGovernance

Safe AI, because you always maintain control

The concern was never the AI. It's the one misfire you can't take back. So we build control in before anything runs. Marshal works only inside scopes you approve, anything sensitive waits for a human signature, and every action leaves a receipt you can read.

Founder-led teams use Marshal

Every founder is thinking the same thing

What's the risk of anunintended action?

The risk is low, but real. We mitigate it with governance. You hold the approvals and the rules.

Marshal ensures

  • Agents operate within the scope you set
  • Document access is decided by you
  • Defined gates with a human in the loop
  • System permissions held by you
  • Active human management, monitoring, and accountability

You define

  • Agent goals and target outcomes
  • Scope and boundaries
  • Rules and procedures
  • System integrations
  • Validation criteria

>>> Sharing & access

Marshal agents are shareable resources

Every agent has owners, collaborators, and viewers. Owners set the rules for tools, prompts, and publishing. Collaborators adjust those rules. Viewers can't change a thing. The sharing model your team uses for documents extends to the AI now doing the work. Nobody has to learn a new system to stay compliant.

See how Marshal runs multiple agents →

>>> Permission enforcement

Marshal checks permissions at every request.

Marshal evaluates permissions the moment an action runs. If a user reaches for data they have no reason to see, the agent refuses, logs the attempt, and tells you exactly why it stopped.

>>> Alignment & scope

Agents perform exactly as designed.

Owners draw the lines: which tools the agent can call, which data it can read, and which actions need a human signature. When something falls outside the scope, the agent stops and routes the request to a person. It never improvises its way around the rules.

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