MixMode, an AI-driven cybersecurity intelligence platform, has closed a $4 million Series A funding round.
Entrada Ventures led the funding round with participation from existing investors, including Keshif Ventures and Blu Venture Investors.
The company plans to use the new funds to expand its AI-powered network traffic analytics platform and fuel the growth of its worldwide network of customers and partners.
According to the Ponemon Institute, over 75% of successful cybersecurity attacks on organization endpoints are due to zero-day attacks. By definition, these emergent attacks cannot be identified by threat intelligence feeds (that focus on lists of historical threats) that most security platforms rely upon.
The MixMode Multi-Stream Cyber Security Monitoring Platform provides deep network visibility and predictive threat detection capabilities, enabling security teams to efficiently perform real-time and retrospective threat detection and visualization.
MixMode’s CTO and chief scientist, Dr. Igor Mezic, created MixMode’s patented technology based on 20 years of experience developing advanced AI technology that has been used for projects with DARPA, the Air Force, Army, CDC, and many others.
Unlike AI used in other cybersecurity solutions, MixMode’s Unsupervised AI acts autonomously, requiring no human training or tuning. MixMode creates a network baseline and delivers zero-day detections within just seven days versus typical ML/AI systems that take anywhere from 6-24 months to train in data, configure and tune. MixMode also constantly refreshes that baseline without manual intervention, so it’s always current and relevant. MixMode is designed for companies that want to leverage AI to improve their security programs and it can be implemented up to 100x faster than other systems.
“MixMode is more than a generation ahead of the adversary. To our knowledge, MixMode is the only Third Wave AI network security monitoring tool currently available,” said Peter R. Stephenson, Ph.D., an AI researcher at the University of Leicester.
Image by mohamed Hassan from Pixabay