Data is at the core of every modern business. With cloud adoption, hybrid work, and countless digital tools, information flows faster than ever: through email, SaaS applications, endpoints, personal devices, and increasingly through AI tools.
This flexibility drives productivity, but it also increases the risks: sensitive information can leave your organisation accidentally (human error, misdirected email) or deliberately (malicious insider, disgruntled employee).
Where once Data Leak Prevention (DLP) was viewed as a “nice to have” security layer; it has since become critical to protect intellectual property, customer information, and compliance-related data.
And with the rapid adoption of Large Language Models (LLMs) such as Copilot and ChatGPT, data can be shared externally in seconds, sometimes without users fully realising the impact. That makes visibility and control more important than ever.
Classic DLP solutions typically start with extensive data classification projects. Every file, every document, every system must be tagged and categorised before the solution can work properly.
However, in reality:
⛔ Few organizations have the resources to classify their data consistently
⛔ The effort is hard to maintain as new data kept being generated
⛔ DLP policies often slow users down, causing frustration and workarounds
On top of that, many traditional solutions are limited to specific platforms or vendor ecosystems, while data today flows across a wide variety of tools, apps, and devices.
The result? Traditional DLP often stayed on paper rather than delivering real protection. Many organizations never unlock the full potential of DLP, leaving blind spots in their security strategy.
With the acquisition of Code42 by Mimecast, a new DLP approach has entered the market. Code42’s Incydr solution focuses on user behaviour and context rather than classification.
Instead of manually labelling every document, Incydr uses AI-driven detection to identify risky data movement, such as files uploaded to personal cloud storage, sent through personal email, or transferred to removable media.
This modern approach makes DLP:
✅ Faster to deploy: No heavy classification project is required
✅ Easier to maintain: AI learns and adapts as data flows evolve
✅ More accurate: Focuses on risky behaviours instead of static file tags
✅ More open: It protects data across almost any environment, not only within a single vendor ecosystem
That last point is key. Companies today rely on a wide mix of tools, platforms, and devices. Modern DLP must follow the data wherever it goes, including interactions with AI tools and LLMs.
This aligns perfectly with modern workplace realities, where the biggest risks are not always sophisticated cyber-attacks, but simple mistakes and insider actions.
At Easi, we want to keep our clients up to date with the latest security evolutions, and make them practical. With Mimecast’s new DLP capabilities, we can now:
Demonstrate the solution in your environment
Explain how it works and how it differs from traditional DLP
Run a Proof of Concept (PoC) so you can see real results with your own data flows
This also means:
✔ You can clearly see where your data is moving today
✔ You can identify risky behaviours before they turn into incidents
✔ You can strengthen your compliance and data protection posture without overwhelming your teams
Ignoring DLP is no longer an option. Beyond the obvious risk of data leaks, organizations today face:
⚠️ Regulatory pressure (GDPR, NIS2, ISO 27001, sector regulations)
⚠️ Financial impact of data breaches (fines, remediation, lost business)
⚠️ Reputation damage that can take years to repair
⚠️ Growing risks linked to AI usage and uncontrolled data sharing
A modern DLP approach like Incydr helps you tackle these challenges proactively, in a way that is realistic, manageable, and aligned with how people actually work today.
| Interested in seeing Incydr in action? 👉Reach out to us. Our experts are happy to set up a demo or PoC tailored to your environment. |