Information security company MIND raised $72 million in a Series B round led by Crosspoint Capital Partners, with YL Ventures and Paladin Capital Group participating.
The round brings the company's total funding to $112 million.
MIND operates in DLP (Data Loss Prevention), but seeks to adapt it to a world where employees and AI agents access and use organizational information in new ways.
What is the problem?
Previously, DLP systems tried to prevent employees from sending sensitive files to the wrong place, copying prohibited information or sharing documents against policy.
Now there is a new channel.
Employees can paste information into AI tools.
Agents can gain access to several systems simultaneously.
API interfaces can transfer data between systems without direct employee action.
The question is therefore not just "is the AI model safe?".
You also need to ask which information enters it, who may use it and what happens when an agent tries to act.
What MIND is trying to do
The company says its system discovers and classifies sensitive information across environments, including SaaS, GenAI tools, AI agent-based systems, endpoints, email and on-premises systems.
It also offers mechanisms to block dangerous actions or remediate exposures.
MIND was founded in 2023.
It presents itself as an information security company connecting DLP and insider risk management with AI use.
The company's numbers
MIND claims its revenue grew 17-fold in the past year and its customer count eightfold.
CEO Eran Barak said the company reached eight-figure annual revenue and serves dozens of customers.
These are company figures, not audited public financial statements.
Why it matters
Many organizations begin AI security discussions by asking which model to choose.
But the information layer matters as much.
Even a secure model can receive information that should not have been sent to it.
Even an agent doing the right task can be given excessively broad permissions.
This is why information security around AI is expected to become more central to organizational implementation projects.
What remains unknown
MIND did not publish its valuation in the round.
It also publishes no public price list or independent benchmark results comparing it with established DLP systems.
It is therefore too early to determine whether its approach is better than existing solutions.
But the problem it seeks to solve is real: as AI gains more information access, permissions management and leakage prevention become infrastructure, not an add-on.