MarTech Pulse Exclusive Interview with Eran Barak, Co-Founder and CEO at MIND

Absolutely. I’m Eran Barak, Co-Founder and CEO at MIND. Over the past two decades I’ve led security, risk and automation programs in highly complex digital environments, and today my focus is ensuring that enterprises can protect what matters most: their sensitive data. At MIND we built a platform to provide Stress-Free DLP, so organizations don’t just check boxes but gain real confidence in their data security journey.

MIND recently unveiled new endpoint DLP innovations. What key enterprise challenges do these updates address?

In enterprise real-worlds, endpoint DLP has too often been clunky, intrusive and disconnected from actual workflow. Our update addresses exactly that: the endpoint is where work happens and where risk often begins. We’ve introduced features that deliver smoother, more integrated protection for endpoint DLP, so teams don’t trade productivity for security. Among the pain-points we’re tackling lack of visibility into data movement, weak native app integration, heavy burden on users and cumbersome remediation workflows.

Read More: The New Era of AI-Driven Marketing Collaboration in E-Commerce Teams

With the new release, we bring full data-lineage visibility at the endpoint, native app protection, USB/peripheral controls, evidence-collection and richer integrations. So, in short: the update helps enterprises move from reactive alerts to proactive, context-aware control of data at the endpoint, without compromising the user experience.

How does the new endpoint module work with MIND’s discovery, classification, and remediation features to deliver unified data protection?

Everything works together as one single, intelligent system rather than disconnected modules. Here’s the workflow:

• First, discovery and classification: we detect sensitive information wherever it lives, including endpoints, using MIND AI, our multi-layer classification engine that supports sensitive data elements like PHI, passwords and CUI.

• Next, endpoint monitoring and protection: the new endpoint agent gives visibility into file and data movement, applications in use, peripheral devices and even collects evidence (screenshots, user actions) when needed.

• Finally, remediation and prevention: when a risky situation is detected, we don’t just alert and stop; we take action. We can automatically adjust permissions, apply labels, write security tags, revoke access or even delete files based on policy.

You get unified data protection across data at rest and in motion, all under one platform. The endpoint isn’t a silo; it’s part of the full lifecycle of protection.

How does MIND balance real-time risk detection with a seamless user experience?

The balance is achieved by focusing on context and automation, rather than blunt rule sets. Legacy DLP tends to flood users with prompts or shuts down workflows. In contrast:

• MIND evaluates user context (role, device, app), data sensitivity and destination or intended use

• We apply proportional response: from soft prompts to hard blocks, depending on severity or data sensitivity level

• All of this is embedded into the endpoint agent and tied to our AI-native, SaaS platform, reducing noise while empowering productivity

We like to call this approach “Stress-Free DLP”, intelligent protection that lets people do their work without getting in the way.

What new risks come with GenAI handling sensitive data, and how does MIND prevent AI-driven exposure?

GenAI introduces new exposure vectors: users pasting sensitive data into prompts, models training on corporate files or unvetted apps accessing data at scale. Endpoints are the vantage points where most of these risks originate.

MIND prevents these risks by securing the data before it reaches the GenAI tool. Our classification and monitoring operate on the endpoint, detecting sensitive data locally and enforcing policy in real-time, regardless of the app in use.

Read More: AI-Powered Content Generation: The New Backbone of E-Commerce Marketing

We also support ecosystem integrations, tags and evidence capture, helping teams understand when, where and how data was exposed so they can intervene early. No need for app-specific allow lists. Our protection is intelligent, context-aware and immediate.

How do you see endpoint DLP evolving in the coming years as organizations balance AI, data privacy, and productivity?

We’re entering what I’d call the “Business-Class Era” of endpoint DLP, where protection is invisible yet intelligent, helping to deliver a stress-free experience. Some trends I foresee:

• Intelligent, intent-aware enforcement that learns and adapts

• Full lifecycle data governance, from origin to action to risk

• Context-aware automation to prevent incidents before they start

• Seamless integration with hybrid, cloud and AI-based environments

• Frictionless user experience with no more forced trade-offs between productivity and security

The endpoint is no longer a bottleneck; it’s a control point for real-time risk mitigation. And that’s the direction MIND is leading in: endpoint DLP that minds what matters, so organizations can move forward with clarity and confidence.

Thank you, Eran, it was a pleasure discussing how MIND is redefining endpoint DLP and helping enterprises protect data without slowing productivity.

Write to us [⁠wasim.a@demandmediaagency.com] to learn more about our exclusive editorial packages and programmes.