Start a pilot

Start with one workflow. Prove the operating model. Expand with confidence.

Focused pathways that take a single AI workflow to governed, provable operation — then scale the pattern.

Engagement pathways

Four ways to begin

Each pathway is scoped to your architecture, team and integrations — grounded in the same govern, execute and prove model.

Enterprises with AI in or near production and no connected view of approval, execution and evidence.

What is delivered: A mapped view of your agents, workflows, controls and evidence gaps against a target operating model.
Evidence produced: A gap analysis document tracing each workflow's current approval, enforcement and evidence state.
What success looks like: Leadership agrees where the control gap is and which workflow to govern first.
The next decision: Choose the first workflow for a Design Partner Pilot.

Teams ready to prove the operating model on one high-value workflow in their own environment.

What is delivered: One workflow taken from design to governed, provable operation — approval, enforcement and local evidence end to end.
Evidence produced: Approved-versus-executed comparisons, governance traces and local execution evidence for the pilot workflow.
What success looks like: The pilot workflow answers the six enterprise questions with connected evidence.
The next decision: Expand the pattern to the next workflows, or harden the pilot for production scale.

Platform teams integrating the in-process SDK and standing up the local evidence store.

What is delivered: The SDK embedded without changing business logic, plus scoped execution profiles and metadata-only capture.
Evidence produced: Working execution events, governance traces and profile resolutions in your environment.
What success looks like: Your engineers operate the SDK and local runtime assurance without vendor hand-holding.
The next decision: Decide the rollout order for remaining applications and environments.

Organisations defining who approves, who operates and who reviews evidence across AI workflows.

What is delivered: An operating model covering approvals, execution bindings, remediation and review responsibilities.
Evidence produced: A documented, role-mapped model your governance forums have signed off.
What success looks like: Approvals and remediation run through named roles instead of ad-hoc decisions.
The next decision: Schedule the first operating-model review against live workflow evidence.

How an engagement runs

A deliberate sequence keeps the first engagement small, real and provable before anything expands.

Understand workflows, risk posture and evidence gaps.

Define scopes, approvals and execution boundaries.

Stand up approvals, bindings and execution profiles.

Run the workflow under Governed AI Execution.

Show approved-versus-executed evidence, kept local.

Every engagement ends with evidence: what was approved, what executed and what supports it.

Get started

Tell us about a workflow you need to govern and we will tailor a focused walkthrough and plan.