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MIND announced a $72 million Series B funding round led by Crosspoint Capital Partners, bringing its total funding to $112 million. The company, which describes itself as an AI-native data loss prevention (DLP) platform, stated it will use the capital to expand into major enterprise markets, strengthen partnerships, and grow its team. MIND reported growing revenue more than 17-fold and expanding its customer base eightfold over the past 12 months while analyzing billions of data events across GenAI and Agentic AI systems. The company also highlighted that it became the first data security firm accepted into Anthropic’s Cyber Verification Program and achieved ISO/IEC 42001 certification for responsible AI.
MIND, an AI-native data loss prevention platform, raised $72 million in a Series B round led by Crosspoint Capital Partners, with continued backing from YL Ventures and Paladin Capital Group. This follows a $30 million Series A raised a year earlier, bringing the company’s total funding to $112 million.
The company stated it will use the funds to broaden its footprint in major enterprise markets, strengthen technology and channel partnerships, and grow its team. MIND reported that over the past 12 months, it grew revenue more than 17-fold and expanded its customer base eightfold while analyzing billions of data events in real time across GenAI, Agentic AI, and conventional IT environments.
MIND’s platform discovers sensitive data across SaaS applications, GenAI and Agentic AI systems, endpoints, on-premise file shares, and email. It uses a multi-layer AI engine to classify files based on content and context, aiming to filter out false alarms and autonomously remediate data exposure. The company recently introduced MIND AI DLP Agents to automate routine DLP operations.
MIND claimed it became the first data security company accepted into Anthropic’s Cyber Verification Program and the first in its field to achieve ISO/IEC 42001 certification for responsible AI. The company cited market research indicating that 90% of enterprises have deployed tools, yet 65% lack confidence in their AI data security controls.
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Чому це важливо
This funding round signals a significant shift in the cybersecurity sector, where traditional data loss prevention tools are being re-engineered to handle the speed and complexity of AI-driven data movement. As enterprises increasingly deploy generative and agentic AI, the risk of sensitive data exposure grows, creating a demand for security solutions that can operate autonomously and in real-time. MIND’s rapid growth and specific focus on AI environments suggest that investors and enterprises view AI-native security as a critical, distinct category rather than a minor update to legacy DLP software. The company’s claim of preventing data loss across hundreds of thousands of endpoints indicates practical deployment at scale, though independent verification of these specific performance metrics is not provided in the source.
The funding highlights a critical gap in enterprise security: traditional DLP tools were not designed for the speed and autonomy of AI systems. As AI agents and generative tools become central to business operations, the risk of data leakage increases, necessitating security solutions that can operate at 'AI speed.'
MIND’s positioning as an 'AI-native' platform suggests a fundamental rethinking of data security architecture, moving from reactive monitoring to proactive, autonomous enforcement. This shift is significant for enterprises that are struggling to maintain control over sensitive data in hybrid AI environments.
The company’s reported growth metrics, including 17-fold revenue growth, indicate strong market demand for these specialized AI security tools. However, these figures are self-reported by MIND and have not been independently audited or confirmed by third-party sources.
The acquisition of ISO/IEC 42001 certification and participation in Anthropic’s Cyber Verification Program may set new benchmarks for trust and compliance in the AI security sector, potentially influencing procurement decisions for other enterprises.
Інтерактивний механізм: як він насправді працює
Дослідіть технологію, що лежить в основі цієї розробки, в інтерактивному режимі.
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Monitor MIND’s expansion into new enterprise markets and the adoption of its MIND AI DLP Agents. Watch for further developments in the integration of AI security certifications, such as ISO/IEC 42001, becoming standard requirements for enterprise vendors. Additionally, observe how other DLP providers respond to the AI-native positioning and whether the market consolidates around these new AI-focused security standards.
Track MIND’s ability to scale its operations and maintain its growth trajectory as it expands into new enterprise markets. The company’s success will depend on its ability to integrate seamlessly with existing enterprise IT stacks while managing the complexity of AI-driven data flows.
Observe the competitive response from established cybersecurity vendors. If MIND’s AI-native approach proves effective, legacy DLP providers may need to accelerate their own AI integration efforts or face market share loss.
Monitor the adoption of AI-specific security certifications. If ISO/IEC 42001 and similar standards become mandatory for enterprise AI deployments, this could create a new compliance layer that affects how AI tools are procured and deployed.
Watch for any independent security audits or case studies that validate MIND’s claims about autonomous remediation and false alarm reduction. Independent verification will be crucial for establishing trust in the AI-native DLP category.