Two-year-old startup,
MIND, is taking a step into the increasingly crowded ring of cybersecurity vendors that offer generative AI-powered data loss and protection (DLP) tools to help corporate security teams strained by increasingly complex data environments, accelerating numbers of alerts, and other challenges.
At the
Black Hat USA 2025 show this week, MIND launched its AI-native DLP platform, designed to automate and continuously inventory sensitive data at rest, user behaviors, agentic AI, and non-human activities. The Seattle-based company claims the platform delivers 91% greater accuracy than legacy DLP tools, reduces false positives and cuts down alert fatigue for security teams and MSSPs.
At the core is the vendor’s MIND AI, a layered classification engine that expands beyond regular expression (RegEx) pattern matching to more finely categorize sensitive file types.
The platform includes out-of-the-box templates for creating business-aligned policies, automated responses and workflows, and integration with remediation platforms to simplify threat response. It provides security for data at rest and protection for data in motion, helping prevent leaks across the IT environment, including generative AI tools, SaaS apps, endpoints, and email. Context-aware controls are built in to help ensure users can follow security policies without disruption.
The Need for Change
The DLP space has been plagued by many challenges with the number and sophistication of cyber threats accelerating. AI holds the promise of easing some of those, particularly as threat actors embrace their own use of AI.
“Many customers are plagued by the shapeshifting task of identifying and protecting their sensitive data as it moves within and even outside of their organization,”
Cloudflare wrote earlier this year. The company uses AI tools in its own DLP Engine. “Detecting this data through deterministic means, such as regular expressions, often fails because they cannot identify details that are categorized as personally identifiable information (PII) nor intellectual property (IP). This can generate a high rate of false positives, which contributes to noisy alerts that subsequently may lead to review fatigue.”
In addition, such a frustrating experience can turn users away from using its DLP product and reduce their overall security posture, Cloudflare wrote.
Cloudflare is among a growing list of vendors, including
Microsoft,
Google Cloud,
Zscaler,
Trellix, and
Fortinet,
using AI in their DLP offerings.
Up and Coming
In June, MIND announced a
$30 million Series A funding round, bringing the total amount raised to $40 million, and stated that since emerging from stealth in October 2024, it had seen 500% customer growth, including some Fortune 1000 companies.
“Data loss prevention is at a breaking point,”
MIND CEO Eran Barak told MSSP Alert. “Enterprises are overwhelmed by data sprawl, alert fatigue and legacy tools that can’t keep pace. Traditional approaches often force security teams into reactive mode, where they chase false positives instead of preventing real threats.”
In March, the company
released a study in partnership with the Enterprise Strategy Group illustrating the struggles organizations are going through with modern DLP tools and the need to modernize them. About 78% of organizations survey said they administering and managing DLP solutions is challenging, and 94% said they are using at least two security tools – and on average, more than three – with DLP capabilities.
In addition, 91% said it’s important to reduce alert noise produced by DLP controls, which are hampered by simple, poor, and outdated classification schemes.
GenAI is the Change
Generative AI is changing that, Barak said.
“By automating data classification and understanding context at machine speed, AI helps organizations accurately identify and protect sensitive data wherever it lives across SaaS, endpoints, GenAI apps, and more,” he said. “AI is essential for navigating the sheer scale and velocity of today’s data. Without it, modern DLP is just ineffective.”
That said, while AI is a huge opportunity in cybersecurity, it needs to be used wisely, with precision and purpose.
“When applied with care … AI amplifies security teams by enabling context-aware classification, reducing manual effort, and remediating risk in real-time,” the CEO said. “Generative AI allows for more dynamic responses, learning from behaviors and continuously adjusting. But it also introduces new identity and access challenges, especially as non-human identities and autonomous agents become more prevalent.”
The technology will go from being helpful to being necessary, given the volume, complexity, and velocity of data has exceeded human scale, Barak said. AI will allow for greater security and scalability.
That goes for MSSPs as well as corporate security teams, he added, noting that they offer the operational scale organizations need. MIND’s autonomous DLP gives MSSPs a force multiplier in the form of a platform that adapts in real time and reduces the burden of managing complex data environments.
