Solution · Data Governance
Know what data you hold, where it lives, and who can reach it.
Classification and protection across your cloud and productivity stack — so sensitive information is handled deliberately rather than by accident.
Is this you?
Built for teams like yours.
- You couldn’t say, today, where your most sensitive data actually sits.
- Files are shared by link and nobody is sure which links are still live.
- You’re subject to GDPR, DPDP or similar and retention is undefined.
- AI tools are now reading company data and you want guardrails first.
What’s included
From “it’s somewhere in the drive” to a defensible position.
Data Discovery
Find where sensitive data actually lives across your cloud and productivity tools.
Classification Scheme
A small, usable set of labels people will apply without being chased.
Access & Sharing Review
External shares, stale links and over-broad permissions found and closed.
Protection Controls
DLP and encryption applied where the data actually warrants it.
Retention Schedule
How long each category is kept, and what happens when that period ends.
Records & Evidence
The documentation you’ll need for a data subject request or an audit.
How it works
From first call to full implementation.
Step 1
Data Mapping
Identify what you hold, where it lives, and which categories are sensitive.
Step 2
Classification Design
Agree a labelling scheme small enough that people will actually use it.
Step 3
Controls & Rollout
Apply protection and sharing rules, then brief the teams affected.
Step 4
Review & Retention
Ongoing checks that classification holds and retention is enforced.
Track record
Real experience, applied to your situation.
15+
Years in IT & security
60+
Countries engaged
5
Continents served
FAQ
Common questions.
Do we need a data classification scheme if we’re only 20 people?
You need a small one. Three or four labels applied consistently protects far more than an elaborate scheme nobody uses. The design work is mostly about keeping it minimal.
Will labelling everything slow the team down?
It shouldn’t. Most classification is automated on the platform side, and the labels people apply by hand are limited to the small number of places where the decision genuinely needs a human.
How does this relate to AI governance?
Directly. Data governance decides what AI tools are allowed to see — most AI data-leakage incidents trace back to classification and sharing that were never defined.
Ready to find out what you’re actually holding?
Free 15–30 minute review. No obligation, no sales pitch.