Information protection
Sensitivity labels and data loss prevention rules — so sensitive content is classified before it leaks, not after.
How a customer protects sensitive content, governs their data across the platforms it lives on, maps their architecture to the regulations that apply, and proves to an auditor that it all holds together.
The standard conversations most organisations have within this domain.
Sensitivity labels and data loss prevention rules — so sensitive content is classified before it leaks, not after.
Microsoft Purview as the catalogue and "where did this number come from?" layer across Microsoft Fabric, Databricks, Snowflake, and other data platforms.
Deciding how long different kinds of content are kept, what gets archived, and what gets safely disposed of — managing information from creation to deletion.
EU AI Act readiness, AI risk register, model cards — governance of the AI estate at the organisation level. Separate from the day-to-day machine-learning lifecycle.
Subject access requests under GDPR, consent management, privacy impact assessments — the everyday privacy work.
Where the conversation needs custom adaptations — regulated, hybrid, or high-stakes.
Mapping the customer's architecture, on a continuing basis, against the regulations that apply — DORA, NIS2, GDPR, HIPAA — so the answer is ready before the auditor asks.
Continuous compliance rather than once-a-year fire drills — Microsoft Compliance Manager as the running evidence layer for SOC 2, ISO 27001, PCI, and similar frameworks.