Protect AI, a cybersecurity firm focused on AI security and machine learning systems, has scored $13.5m in seed funding.
The company raised the capital as it came out of stealth and launched its first product, NB Defense.
Protect AI claims NB Defense is the industry’s first security solution to address vulnerabilities in a core component used at the beginning of the machine learning supply chain – Jupyter Notbeooks.
This is a rapidly growing security issue which is increasing significantly annually as more organizations move machine learning into production environments. Today, there are over 10m publicly accessible notebooks, growing by 2m+ annually, with many more in private repositories.
The funding round was co-led by cybersecurity investors Acrew Capital and boldstart ventures. Mark Kraynak and Ed Sim, respectively, join the Protect AI Board of Directors. Additional investors include Knollwood Capital, Pelion Ventures, Avisio Ventures, and experienced cybersecurity leaders Shlomo Kramer, Nir Polak, and Dimitri Sirota.
Protect AI CEO and co-founder Ian Swanson said, “As enterprises put AI/ML in production it must be protected commensurate with the value it delivers. I have seen more than one hundred thousand customers deploy AI/ML systems, and realized they introduce a new and unique security threat surface that today’s cybersecurity solutions in the market do not address.
“This is why we founded Protect AI. ML developers and security teams need new tools, processes, and methods that secure their AI systems. Since nearly all ML code begins with a notebook, we thought that’s the most logical place to start so that we can accelerate a needed industry transition. We are launching a free product that helps usher in this new category of MLSecOps to build a safer AI-powered world, starting now. But, we have many more innovations that will be released quickly across the entire ML supply chain.”
Protect AI advisory member Dan Plastina added, “This gap in coverage means that a critical portion of an enterprise’s code base could contain unseen vulnerabilities, creating zero-day exploit risks. Unfortunately, having worked with hundreds of customers, I’ve learned that ML code is not commonly scanned today in enterprises. Furthermore, ML specific scanning and AI vulnerability remediation is not yet a priority for most CISOs.
“This is because tools have not existed to target this specific need while catering to both AI builders and cybersecurity professionals, until now. Protect AI addresses that gap.”
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