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MIND Locks Down $72 Million to Redefine How Enterprises Track and Protect Sensitive Data

MIND Locks Down $72 Million to Redefine How Enterprises Track and Protect Sensitive Data

Data is leaking out of enterprises faster than most security teams can track it — and a Tel Aviv-based startup thinks it has the architecture to stop that. MIND, an Israeli cybersecurity company specializing in data loss prevention (DLP), has raised $72 million in a funding round that signals serious investor conviction in a sector that legacy tools have long failed to adequately protect. The raise puts MIND among the better-capitalized pure-play AI safety and data security companies operating today.

According to Globes reporting, the round positions MIND to scale its platform internationally and double down on enterprise customers who need continuous, real-time visibility into where sensitive data lives, moves, and gets exposed across their organizations.

a large enterprise network operations center with multiple screens displaying data flow maps and alert dashboards, no people in the foreground

What MIND Actually Does Differently

Traditional DLP tools were built for a different era — one where data mostly stayed inside a corporate perimeter. Cloud storage, SaaS applications, remote workforces, and generative AI tools have shredded that perimeter entirely. Sensitive files now flow through Slack, Google Drive, ChatGPT plugins, and dozens of other channels that legacy DLP systems were never designed to monitor coherently.

MIND’s approach centers on automated data discovery and classification, continuously scanning across an organization’s entire data estate — cloud and on-premise — to understand what sensitive information exists and whether it’s at risk of exposure. Rather than relying on static rules that security teams have to manually update, MIND uses AI to surface risky behaviors and misconfigurations in real time, reducing the operational burden on already-stretched security operations teams. That distinction matters enormously in a threat landscape where misconfigured cloud buckets and accidental oversharing routinely cause breaches that attackers never even need to engineer.

close-up of a secure cloud data architecture diagram on a monitor in a dimly lit server room, showing encrypted data pathways and access control nodes

The Market Timing and What’s at Stake

The $72 million raise arrives at a moment when enterprise demand for modern DLP is surging, driven in large part by the explosive adoption of generative AI tools inside companies. Security and compliance teams are grappling with a new class of data exposure risk: employees pasting proprietary code, customer data, or financial records into AI assistants, with little visibility into where that data ends up. Regulators in the EU, US, and elsewhere are beginning to tighten requirements around data handling, adding compliance pressure on top of the security imperative.

MIND’s funding trajectory also reflects a broader venture trend of backing cybersecurity infrastructure plays that sit at the intersection of AI and enterprise risk. Investors are increasingly willing to write large checks for platforms that can demonstrably reduce operational friction for security teams — not just add another alert to the pile. For context on how aggressively capital is chasing AI infrastructure right now, Crusoe recently locked in AI data center commitments worth $3.9 billion, illustrating the scale of investment flowing into AI-adjacent infrastructure across the board.

With $72 million now in hand, MIND has the runway to expand its sales footprint in North America and Europe, deepen integrations with major cloud providers, and build out the engineering capacity needed to stay ahead of an increasingly complex threat surface. In a market littered with legacy vendors and incremental improvements, that’s a meaningful head start.

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