What we assess
Business goals
Outcomes leadership wants from analytics and AI.
Priority AI use cases
Workshop-driven shortlist with risk and feasibility scoring.
Data-source inventory
Systems, ownership, criticality and integration patterns.
Data quality
Freshness, completeness and reference-data integrity.
Integration gaps
Where federation, pipelines or APIs are missing.
Identity and permissions
Account model, conditional access and group hygiene.
Sensitive-data exposure
Oversharing, classification and DLP coverage.
Governance and ownership
Data owners, stewards and decision rights.
Reporting maturity
Current BI footprint, trust and adoption.
Architecture
Current and target-state data architecture.
AI security
Guardrails, retrieval filtering, prompt-injection protections, logging.
Operating model
Roles, run book, change management and managed services fit.
What you receive
Data maturity score
AI readiness score
Data-source map
Risk and dependency register
Priority use-case matrix
Target architecture
Zetaris suitability recommendation
30-, 60- and 90-day roadmap
Executive briefing
Engagement flow
- 1
Kickoff
Goals, stakeholders and scope confirmation.
- 2
Discovery
Interviews, source inventory and document review.
- 3
Analysis
Maturity, risk, gaps and architecture review.
- 4
Roadmap
Prioritized initiatives with sequencing and dependencies.
- 5
Executive Briefing
Findings, recommendations and next-step engagements.