aiqbench takeAI Safety

This funding round highlights the critical shift in data loss prevention (DLP) from managing human-paced workflows to securing autonomous AI agents that operate without direct human oversight. The core issue addressed is the systemic risk of sensitive enterprise data leaking into public AI models, a vulnerability exacerbated by the fact that 65% of companies feel their current controls are inadequate for this new paradigm. As organizations deploy AI-native security tools like MIND's agents to classify and block risky activities in real-time, the industry faces a fundamental rearchitecture of governance around machine-driven data flows.

Sources coveringSiliconANGLE, Latent Space, AWS

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Mind raises $72M to stop sensitive data leaking into AI tools

SiliconANGLESeptember 17, 20264 min read

Data loss prevention startup Mind Security Inc. today announced it has raised $72 million in new funding to push further into large enterprise accounts with new hires and channel partnerships. Mind provides software that locates sensitive files wherever an organization keeps them, in software-as-a-service applications, on endpoints and in email, then classifies each one on […] The post Mind raises $72M to stop sensitive data leaking into AI tools appeared first on SiliconANGLE.

Data loss prevention startup MIND Security Inc. today announced it has raised $72 million in new funding to push further into large enterprise accounts. Hiring and channel partnerships will absorb much of the money. MIND provides software that locates sensitive files wherever an organization keeps them, in software-as-a-service applications, on endpoints and in email, then classifies each one on content as well as context. Controls sit on top…

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