Enforcement that agents can't bypass.

• Watching isn't stopping.

  Most AI security tools fire an alert after the agent has already moved money, exfiltrated data, or dropped the table. By the time anyone reads the log, the action is done.

• Asking the model nicely isn't a control.

  Telling an agent to refuse in its instructions is a suggestion, not a guarantee. Anything that nudges the model — a clever prompt, a new model version, a bad day — routes around it.

• Dashboards aren't decisions.

  You can record everything an agent does and still let the next bad action through. Auditors want a control. Observability is evidence at best.

Agents are now spending money, merging code, and changing customer records inside enterprises. The controls that worked when humans were in the loop assume a slow, accountable person on the other end. That assumption is gone.

• Instructions in the prompt

  A request to the model. No enforcement at all.

  Stops the action

  —

  Holds up under attack

  —

  Audit a regulator trusts

  —

  Covers every surface

  —

• Monitoring and detection

  Sees the action. Records it. Doesn't stop it.

  Stops the action

  —

  Holds up under attack

  Audit a regulator trusts

  —

  Covers every surface

• Device-level controls

  Blocks on the laptop. Blind to everything the agent does off it.

  Stops the action

  Holds up under attack

  Audit a regulator trusts

  —

  Covers every surface

  —

• Auctra

  Decides before the action lands. Across every surface. With an audit trail you can defend.

  Stops the action

  Holds up under attack

  Audit a regulator trusts

  Covers every surface

• Watch

  Auctra is in the path of every action an agent tries to take — across the surfaces enterprises actually deploy on.

• Decide

  A policy you set decides what's allowed before the action happens. Same situation, same answer, every time.

• Prove

  Every decision is recorded in a log you can hand to a regulator, an auditor, or a board — and replay step by step.