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Frenos Raises $3.88M in Seed Funding for OT Security Assessment Platform

Frenos, a company that has developed an autonomous OT security assessment platform, has raised $3.88 million in seed funding. 

Frenos, a startup that has developed an autonomous operational technology (OT) security assessment platform, announced on Tuesday that it has raised $3.88 million in seed funding. 

The funding round was led by DataTribe and will help Frenos accelerate the development of its platform and expand the firm’s go-to market presence across critical infrastructure sectors. 

Frenos has developed an AI-native platform designed to assess, prioritize and protect mission-critical environments without the risk of causing operational disruption. 

The platform uses a digital network twin and an AI reasoning agent to analyze the ways threat actors could target an organization’s OT environment. Customers are shown exactly which combinations of TTPs and vulnerabilities can pose the greatest risk to their specific setup, and they are provided with tailored recommendations for reducing risks. 

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“The Frenos team brings something rare to OT security: the perfect combination of operator security experience and breakthrough innovation,” said Robert M. Lee, CEO and co-founder of industrial cybersecurity giant Dragos and Frenos advisory board member. 

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Lee added, “Frenos is ushering in the next-generation of OT security defenses, and it arrives when all critical infrastructure organizations need help driving data driven insights to make the best choices with their limited OT resources.”

In addition to Dragos, Frenos has partnered with cybersecurity companies Claroty, Palo Alto Networks, Tenable, Rapid7, Forescout, Nvidia, and Enaxy. 

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Related: Xona Raises $18 Million for OT Remote Access Platform

Written By

Eduard Kovacs (@EduardKovacs) is senior managing editor at SecurityWeek. He worked as a high school IT teacher before starting a career in journalism in 2011. Eduard holds a bachelor’s degree in industrial informatics and a master’s degree in computer techniques applied in electrical engineering.

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