Business Challenges

As the organization accelerated its digital and AI transformation, it faced growing risks related to data governance, regulatory compliance, and information protection:

1. Sensitive financial and HR data was distributed across Microsoft 365, Azure, and emerging Fabric workloads
2. Existing data classification and retention practices were inconsistent and largely manual
3. Preparing for Copilot and AI workloads raised concerns around data leakage, insider risk, and regulatory exposure
4. Compliance requirements demanded alignment with financial-services regulations and data-privacy standards
5. Security controls needed to scale without slowing innovation or user productivity

The organization required a secure-by-design compliance architecture that would support AI readiness while maintaining regulatory confidence.

atQor Solution

atQor designed and delivered a Microsoft Purview–led security and compliance architecture, embedding governance directly into the customer’s Microsoft ecosystem rather than layering it as an afterthought.

Key elements of the solution included:

1. Microsoft Purview Information Protection
   1. Classification and sensitivity labeling of financial, HR, and operational data
   2. Tenant-wide policy enforcement across Microsoft 365, SharePoint Online, OneDrive, and Fabric
2. Data Loss Prevention (DLP) & Insider Risk Management
   1. Automated detection of risky downloads, external sharing, and abnormal access patterns
   2. Real-time alerts and enforcement aligned with compliance policies
3. Data Lifecycle & Retention Management
   1. Policy-driven retention, archival, and deletion mapped to regulatory obligations
4. Copilot & AI Readiness Architecture
   1. Secure Copilot enablement framework grounded in Purview, Entra, and Microsoft security best practices
   2. Governance checkpoints embedded into AI adoption planning
5. Cross-Platform Governance
   1. Unified compliance boundary across Microsoft 365, Azure, and Microsoft Fabric
   2. Role-based access aligned with organizational identity models

The engagement was delivered through a structured assessment-to-implementation approach, aligned with Microsoft security guidance and best practices.

Outcomes & Business Impact

1. 100% of financial and HR content classified and governed
2. 82% reduction in risky document sharing after DLP enforcement
3. Cleared internal security and compliance audits for AI and Copilot readiness
4. Improved regulatory alignment with financial-services data protection standards
5. Faster AI adoption enabled by secure, governed data foundations
6. Reduced operational risk without impacting user collaboration or productivity

Why It Matters

By embedding compliance into the core of its data and collaboration platforms, the organization transformed security from a constraint into an enabler of AI innovation. The solution ensured that future Copilot and analytics initiatives could scale confidently—without retrofitting controls later.

This approach established a repeatable compliance backbone supporting long-term AI, analytics, and digital modernization initiatives.