Data & AI Governance
Increase trust, control, quality, and compliance
NeoStats builds governance into the operating model - not as a compliance overlay, but as the infrastructure that makes data and AI trustworthy at enterprise scale.
Why it matters
Data governance is not a reporting exercise. NeoStats implements ownership models, metadata frameworks, data quality controls, and responsible AI guardrails - so every data product is auditable, secure, and usable.
What NeoStats delivers
- Microsoft Purview data catalogue, lineage, and classification
- Data ownership and stewardship operating model
- Data quality rules, profiling, and monitoring
- Master data management (MDM) implementation
- Responsible AI policy, explainability, and guardrail frameworks
- Regulatory and compliance alignment (ISO 27001-aligned delivery practices)
Where it applies
- BFSI organisation with fragmented data ownership and audit exposure
- Enterprise needing Purview-based lineage and classification
- Organisation preparing for DORA, GDPR, or sector-specific compliance
- Team deploying AI and needing responsible AI governance from day one
Delivery highlights
- Governance framework that scales without requiring a large central team
- Data quality dashboards visible to data owners, not just IT
- Responsible AI policy embedded in model deployment workflow