AI Governance

Govern agentic AI without giving up control

Autonomous agents are only as safe as the controls around them. We wrap every model and tool call in policy, approvals, and immutable lineage — all inside your own perimeter.

  • Policy-enforced action layer
  • Model & prompt governance
  • End-to-end decision lineage
  • Audit-ready by design
0
data leaving your perimeter
100%
of agent actions logged with lineage
SOC 2 / ISO
control families mapped out of the box
<1 run
to reconstruct any decision end to end
// the control plane

What governance actually covers

Six layers that turn an autonomous agent from a liability into an auditable system of record.

// how we instrument it

From open-loop agent to governed system

We retrofit controls onto agents you already run, or build them in from day one.

01

Map

Inventory every action an agent can take and assign each a risk class and required approver.

02

Gate

Wrap tool calls in the policy layer — credentials, limits, and approval rules enforced at the boundary.

03

Record

Stream immutable lineage for every run to logs and your SIEM, never to an outside service.

04

Attest

Map controls to your frameworks and generate the evidence auditors and regulators ask for.

// non-negotiable

Your data never leaves your perimeter

Most governance pitches are really dashboards that quietly route your prompts and documents through someone else's infrastructure. That is not governance — it is a second data-exfiltration path with a nicer UI.

We instrument agents where your data already lives: on-prem, in your VPC, hybrid, or fully air-gapped. The policy engine, the lineage store, and the eval harness all run inside your boundary, under credentials you control and rotate.

  • On-prem, VPC, hybrid, or air-gapped deployment
  • Lineage and telemetry written to logs you own
  • Scoped, rotatable credentials per agent and tool

Ungoverned agent vs. governed agent

The difference between a clever demo and something you can put in front of an auditor.

Ungoverned agentGoverned by Automatic.co
ActionsExecutes freely with broad credentialsGated by risk class, scope, and limits
High-risk stepsRuns them automaticallyPause for human approval
TraceabilityScattered logs, if anyImmutable end-to-end lineage
Data pathOften through a vendor cloudStays inside your perimeter
ComplianceManual scramble at audit timeControls mapped, evidence on demand

Related security & infrastructure

Governance works alongside the rest of the private-AI stack.

Frequently asked questions

Does any of our data leave our environment under your governance model?

No. Governance is designed around your perimeter: agents run on-prem, in your VPC, or air-gapped, and prompts, retrieved context, and outputs stay inside it. Telemetry and lineage are written to logs you own — nothing is shipped to a third-party dashboard.

How do you stop an agent from taking an action it shouldn't?

Every tool call passes through a policy-enforced action layer. Each action carries a risk class, scoped credentials, and rate and spend limits. High-risk steps require human approval, and anything outside policy is blocked and routed to an exception queue rather than executed.

Can we prove what an agent did for an auditor?

Yes. We capture immutable decision lineage for every run — the prompt, model and version, retrieved sources, each tool call and its result, approvals, and the final action. It exports to your SIEM and produces audit-ready records mapped to SOC 2, ISO 27001, HIPAA, or your internal control framework.

Which controls map to compliance frameworks?

Access scoping, change management, logging, and human review map directly to SOC 2 and ISO 27001 control families; data-residency and PHI handling map to HIPAA and GDPR. We document the mapping so your existing audit program covers the agents too.

Put your agents under controls you can defend

Bring one agent you already run. We'll map its actions, show you the gaps, and the lineage it should be leaving behind.