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AI agents that act inside guardrails

Tool-using agents that triage, route and follow up inside written guardrails, with an audit log and a kill switch.

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Blueprint of a branching decision tree: a cube enters a gate and routed lines fan out through further gates to a row of cubes

What you get

  • A scoped inventory of every action the agent can take
  • Escalation and approval rules written into code
  • An audit log of every action, searchable after the fact
  • A kill switch, a rollback path and a shadow-mode period

How it works

  1. 1

    Working session

    Thirty minutes. You bring one process, we map what it would take.

  2. 2

    Assessment

    One to two weeks. We measure the baseline and rank the options.

  3. 3

    Build

    Four to eight weeks. We ship into production on your stack.

  4. 4

    Run

    Monthly and optional. Monitoring, evaluation runs, upgrades, the next use case.

Questions

What is the difference between an AI agent and an automation?+

An automation runs a fixed sequence you defined. An agent chooses which tools to call based on what it finds, inside limits you defined. We use agents only where the branching is genuinely open-ended.

How do you stop an agent doing something damaging?+

Four layers: an agreed tool list, approval queues for high-consequence actions, a log of every action with its inputs, and a kill switch tested during the build rather than after an incident.

How long before an agent runs unattended?+

The build is typically four to eight weeks, then shadow mode runs for a period you choose. During it the agent proposes actions against live input and takes none.

Related

  • Workflow Automation Platforms→
  • AI Integration→
  • Logistics & Supply Chain→

Bring one broken process.

No discovery marathon. Bring one process that costs your team hours and we will map what an integration would look like in a free 30-minute working session.

Book a working session→