MixMode

MixMode is a network detection and response (NDR) vendor built around unsupervised, self-learning AI rather than the signature- or rules-based detection that dominates most of the network monitoring market. The pitch is that its models continuously build a statistical baseline of what “normal” looks like for a given network without needing labeled attack data or predefined rules, then flag deviations in real time, an approach aimed at catching novel and zero-day attack patterns that signature-based tools by definition can’t recognize until a signature exists. The company was originally founded as PacketSled before rebranding to MixMode as it shifted its core technology toward this unsupervised, context-aware modeling approach.

MixMode sells primarily to mid-market and enterprise security operations teams that want AI-driven anomaly detection layered on top of, or in place of, traditional NDR and SIEM correlation rules. Its differentiation claim rests on reducing the alert-tuning burden that plagues rules-based NDR tools, since a self-learning baseline in principle needs less manual signature maintenance than a rules engine does. That claim is inherent to the unsupervised-learning category broadly and is not unique validation of MixMode’s specific implementation.

The company raised a $45 million Series B led by growth-equity firm PSG, with participation from Entrada Ventures, bringing total funding to roughly $69.6 million. It is headquartered in Santa Barbara, California, a smaller AI/security hub than the Bay Area or Austin, and operates as a specialist, single-product NDR vendor rather than a broader security platform.