MixMode Raises $4 Million in Series A Round Led by Entrada Ventures

Christian Wiens Director of Marketing

Christian Wiens is Director of Marketing at MixMode. He has 10+ years of experience as a cybersecurity professional. He has his BA from The University of California, Berkeley and resides in Austin, TX.

Today we announced the completion of our Series A round of funding, raising a total of $4 million led by Entrada Ventures. The round included participation from existing investors including Keshif Ventures and Blu Venture Investors. The new funding will be used to expand MixMode’s AI-powered network traffic analytics platform and to fuel the growth of our worldwide network of customers and partners.

“Large enterprise security teams urgently need a solution to identify zero-day threats,” said John Keister, CEO at MixMode. “Our predictive analytics platform is solving this massive problem for clients today. We are excited to continue our growth path and we are fortunate to be working with an experienced partner like Entrada on our journey.”

According to a report by 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. MixMode’s AI is built to baseline a network in seven days and surface zero-day, non-fingerprinted attacks in real-time.

MixMode’s cybersecurity platform is designed to be a single pane of glass for security analysts. The MixMode platform brings in multiple streams of data including network data, public cloud data and feeds from existing security tools such as endpoint, firewall, and SIEM. The MixMode Network Traffic Analytics platform is the first cybersecurity platform to leverage “Third Wave” AI (as defined by DARPA), utilizing an advanced unsupervised learning model to address major security issues facing cybersecurity teams today. The platform’s ability to leverage AI to build a network baseline and to predict the network’s future activity make it uniquely powerful in identifying emerging threats.