Classification and protection
Make sensitive information carry its controls with it.
UNIFY helps organisations implement Microsoft Purview Information Protection so labels, encryption, classification, and governance rules follow sensitive content across collaboration and data workflows.
Operating problem
Information protection needs more than labels.
Labels only help when people understand them, automation applies them sensibly, and downstream controls match the sensitivity of the content.
UNIFY helps organisations design the classification model, protection rules, adoption path, exceptions, and governance practices needed to make Microsoft Purview Information Protection useful in daily work.
Where UNIFY helps
Turn classification into an operating control.
We help define sensitivity labels, publishing policies, encryption settings, auto-labelling, user education, data discovery, reporting, and exception handling so information protection supports both security and delivery.Information discovery
Identify sensitive information types, storage locations, ownership, and handling expectations.
Label taxonomy
Design a sensitivity model that is understandable, enforceable, and aligned with obligations.
Protection design
Map labels to encryption, access, sharing, and usage controls that match real risk.
Auto-labelling
Use detection and simulation to apply labels where automation is reliable and defensible.
Adoption support
Help users understand labels, policy tips, exceptions, and safer collaboration behaviours.
Governance reporting
Monitor label use, exceptions, sensitive data exposure, and improvement actions over time.
Outcomes
Data protection that keeps context.
A mature information protection model makes sensitive content easier to identify, safer to share, and more governable across Microsoft 365, endpoint, cloud, and AI-enabled workflows.Clearer data handling
Give people and systems a shared signal for how sensitive information should be treated.
Persistent protection
Keep controls attached to sensitive content as it moves through collaboration and storage locations.
Better compliance evidence
Connect classification and protection activity to privacy, regulatory, and internal governance needs.
Safer AI readiness
Improve data hygiene and sensitivity signals before content is exposed to AI-enabled workflows.
Reduced manual effort
Use auto-labelling and policy design to reduce reliance on manual classification alone.
More durable governance
Maintain labels, policies, reports, and exceptions as information risk changes.
Next step