Intake summary
System/workflow name, owner, approver, business purpose, users, and current rollout stage.
First deliverable
AI Onboarding Evidence Pack.
The reviewable package your approvers can actually sign before an AI assistant, RAG workflow, Copilot rollout, or agent system expands.
Purpose
Turn a messy AI onboarding plan into a decision-grade candidate.
The pack records the system purpose, approved source classes, excluded source classes, sensitivity notes, validation plan, human approval gates, evidence status, and a DecisionCard. If required evidence is missing, the pack says so instead of pretending the rollout is ready.
Buyer result
A clear artifact showing what the AI may use, what it must not use, and what has to be reviewed before activation or expansion.
Pack contents
What goes into the first artifact.
Approved sources
Source classes, source owner, business purpose, sensitivity, inclusion reason, and freshness expectations.
Excluded sources
Material that must stay out, exclusion reason, risk if included, owner/approver, and future approval path.
Validation plan
Questions the AI should answer from approved context and refusal/escalation checks for excluded context.
Human gates
Approval before import, activation, expansion, tool/action enablement, external sharing, and baseline advancement.
Evidence status
Decision-grade candidate, preliminary, blocked, or non-decision-grade with missing evidence listed clearly.
Example
Maintenance operations assistant.
The public-safe example shows a property management company preparing an assistant for maintenance SOPs, vendor contacts, escalation matrices, emergency response steps, and tenant communication templates while excluding leases, ledgers, HR, legal, payment records, and private inboxes.
View the example
Use the sample page to see how the pack structure communicates approved context, exclusions, validation questions, and human gates without exposing internal mechanics.