Choose the job
Define a bounded user need, authority, outcome, and unacceptable failure.
Solution path
Prepare business data for AI
Build the governed sources, definitions, permissions, and feedback a specific AI capability requires.
The situation
AI initiatives expose data limitations quickly. The useful response is not a vague enterprise-cleanup program, but a minimum dependable foundation for the intended job.
What teams notice
Signals that the current path needs attention
- A prototype relies on manual exports
- Source permissions are implicit
- Business terms are inconsistent
- There is no representative evaluation or feedback record
What changes
Resolve the system, not only the symptom
Map the data path
Identify approved sources, definitions, permissions, freshness, and deletion behavior.
Build the foundation
Implement only the integration, model, retrieval, and feedback the capability needs.
Evaluate in context
Test the end task with representative cases before widening use or authority.
Intended outcomes
A stronger operating path
- A grounded readiness decision
- Dependable and permissioned context
- A bounded first capability
- Evaluation and operating ownership
Anonymized proof
AI is positioned as one consumer of a dependable data system, following the same source, definition, permission, and review discipline required by reporting.Explore representative work
Questions
What teams often ask first
Do we need to clean all company data first?
No. Address the sources, definitions, permissions, and feedback required by the intended capability.
Can the result be that AI is not appropriate?
Yes. Ordinary software, reporting, workflow automation, or process repair may be the stronger recommendation.