AI governance · Real usage

Useful AI governance starts from real uses, not from a generic policy.

Robinswood structures governance around your flows, risks and responsibilities so AI remains controllable and maintainable.

  • AI use register and risk level;
  • decision and escalation roles;
  • simple rules for data, tools and validation;
Assess my AI governanceCheck if it fits

30 minutes

First conversation: maturity level and priority angle.

In 30 minutes, we identify whether your urgency is use inventory, risk register, policy or operational steering.

Fast qualification

  • Human reply within 24–48 business hours
  • No tool selling before diagnosis
  • Short form, enough context
Initial response within 24–48 business hours
No automated sales follow-up after the form
Not an ERP, RPA or n8n reseller

Get a first opinion on your AI constraint

In 30 minutes, the goal is simple: understand your main blockage and decide whether a deeper diagnosis is worth engaging.

Short form

Short form, enriched just enough to qualify ICP/budget fit before the conversation.

Optional but useful to qualify SME/mid-market fit, budget and priority immediately.

One sentence is enough. We qualify the context later.

Initial response within 24 to 48 business hours
If the topic is relevant, we suggest a 30-minute executive diagnosis.
Data is only used to process your request. No automated sales sequence.

Your governance is fragile if

  • AI uses already exist but are not inventoried;
  • no one knows who validates sensitive use cases;
  • data rules vary across teams;
  • expected gains are not monitored;
  • compliance, IT and business teams move separately.

What the framing produces

  • AI use register and risk level;
  • decision and escalation roles;
  • simple rules for data, tools and validation;
  • 30 to 90 day governable adoption plan.

Best fit

  • leadership teams that want to industrialize without chaos;
  • IT, business and compliance functions;
  • organizations moving from informal AI tests to durable uses.

Preuve terrain

The frame must survive daily work

In a mid-market company, AI governance became operational by connecting each use case to an owner, allowed data, validation level and gain indicator. The topic moved from theory to management.