Company-controlled AI delivery proof
Inspect the deployment patterns, launch criteria, and operating artifacts behind company-controlled AI for critical workflows.
Proof hierarchy
Outcome proof is strongest, but before that exists buyers should inspect concrete delivery proof: architecture, launch criteria, review steps, evaluation, and change control.
Inspectable artifacts
The delivery proof should include a decision brief, week-2 architecture pack, pilot launch pack, and monitoring or change log.
- The decision brief names the first workflow, owners, company-control boundary, and reason to pilot now.
- The architecture pack covers hosting setup, model choice, tuning plan, and success criteria.
- The launch pack covers human review, backup logic, operator handoff, and live-work readiness.
- The change log records what changed, who approved it, what was retested, and how quality, review load, and cost moved.
Controlled workflow package
A controlled workflow package should make the trigger, AI step, human approval, system output, evaluation frame, operational visibility, and governance path easy to inspect.
Governance and change control
Prompt, policy, threshold, model, and hosting changes should have a traceable owner, approval, retest path, and rollback rule before expansion.
Next step
Request Workflow Review when the workflow and owners are clear, or use the Workflow Fit Assessment to score fit before a buying conversation.