Scope a data build SERVICE 03 / GOVERN BEFORE YOU GENERATE
Make your data ready before AI speaks for the business.
Connection is not comprehension. AI still needs approved entities, shared definitions, current data, access boundaries, evaluation criteria, and a person responsible for the outcome. We prepare that decision context first, then build or enable only the AI workflow the team can govern.
01 / QUESTIONS
The answer should survive the meeting.
What definitions, data, and tools may the workflow use—and what is off limits?
How will we evaluate a useful answer, detect failure, and route uncertainty to a person?
02 / FAULT LINES
Find where trust breaks before choosing the tool.
Undefined context
The warehouse contains tables, but business entities, metric rules, and decision boundaries are not documented for reliable interpretation.
Uncontrolled access
A connected model can reach data or tools without a clear permission model, usage policy, audit trail, or ownership path.
No evaluation loop
A fluent answer appears useful, but there is no test set, acceptance criterion, monitoring plan, or escalation route when it is wrong.
03 / SCOPE
Responsible AI begins with a governed decision contract.
Assess readiness
Select a bounded use case and identify the gaps between today’s data environment and the evidence the workflow needs.
- Use-case and decision-risk assessment
- Data, semantic, and process gap review
- Readiness gates and ownership
Prepare the context
Expose only the governed models, definitions, metadata, and tools required for the approved task.
- Approved metrics and semantic context
- Governed MCP resources, tools, or CLI commands when useful
- Permissions, provenance, freshness, and audit metadata
Evaluate and operate
Define what a good answer means before release, then monitor usage and keep people in control of consequential decisions.
- Test cases and acceptance criteria
- Usage and quality monitoring
- Human review and escalation paths
04 / SOURCE TO DECISION
AI is the final enabled layer—not the foundation.
Potential deliverables can include governed question-answer interfaces, narrative reporting, metric assistants, anomaly triage, scoped MCP servers, or purpose-built CLI workflows. We recommend them only when the underlying data, access, evaluation, and ownership gates are ready for the intended decision.
Instrument
Define the events, entities, consent, and identity behavior the decision requires.
Warehouse
Bring useful source data into an owned analytical environment with freshness controls.
Model
Create tested definitions for customers, orders, contribution, cohorts, and other business concepts.
Decide
Deliver governed answers through scorecards, analysis, alerts, briefs, or custom interfaces.
Enable AI
Expose approved data to evaluated AI workflows with permissions and human escalation.
START WITH THE EXPENSIVE UNKNOWN
Bring us the answer you don’t trust.
We’ll review the question and follow up to determine whether a focused teardown is the right next step. The first job is locating the break: collection, modeling, governance, or delivery.