WHY HERDING CATS

Autonomy needs a control plane.

Autonomy needs a control plane.

AI agents are gaining access to enterprise data, tools and business systems. As they move from generating answers to taking actions, organisations need a way to control what those agents are allowed to do — before consequential actions happen.

THE CONTROL GAP

AI agents are gaining authority faster than enterprise controls are adapting.

AI agents are gaining authority faster than enterprise controls are adapting.

Too much happens after the fact

Monitoring can tell you what an agent did. In high-risk environments, organisations also need to control whether the action should happen at all.

Fragmented controls

Identity, permissions, policies and approvals are often spread across different models, frameworks and enterprise systems.

More autonomy

Agents are moving from assistants to actors that can change data, trigger workflows and interact with customers.

OUR APPROACH

Monitor agent activity. Control what they do next.

Monitor agent activity. Control what they do next.

Herding Cats is designed to sit in the agent execution path, evaluating consequential actions before they reach enterprise systems — allowing, blocking, escalating or routing them for approval.

HUMANS WHERE THEY MATTER

Automate the routine.
Human oversight where it matters.

Automate the routine.
Human oversight where it matters.

Regulated organisations need human oversight without turning every agent action into a manual review. Herding Cats uses policy, context and risk to focus human attention where judgment actually matters.

WHY WE’RE DIFFERENT

Built as infrastructure for agent control.

Built as infrastructure for agent control.

Runtime governance

Control actions before execution.

Risk-based oversight

Escalate decisions that need judgment.

Vendor-neutral

Govern across models, frameworks and systems.

Compliance-aware

Capture ownership, decisions and evidence.

See what governed autonomy looks like.

See what governed autonomy looks like.

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