MixMode provides an AI‑native cyber threat detection platform that autonomously learns the normal behavior of each network using patented dynamical‑systems mathematics, enabling real‑time detection of known and unknown attacks without historical data or large GPU resources. The solution deploys in under an hour across on‑premise, cloud, hybrid, and air‑gapped environments, delivering explainable alerts that reduce alert fatigue and improve SOC analyst efficiency.
Funding
$45M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
PEFounders
Product
Problem
Traditional security operations rely on signature-based and rule-based tools that require extensive historical data, constant retraining, and high GPU resources, making it difficult to detect novel or stealthy cyberattacks—especially in air‑gapped, DDIL, or OT environments.
Solution
MixMode offers an AI‑native cyber threat detection platform that autonomously learns the normal behavior of each network using patented dynamical‑systems mathematics. By continuously forecasting expected activity, the system flags deviations, including the absence of expected traffic, that indicate pre‑attack indicators or active malicious behavior. The platform operates in real time across on‑premise, cloud, hybrid, and disconnected deployments without needing large GPU clusters or historical baselines. It reduces alert fatigue through explainable AI that distinguishes known threats from novel anomalies, providing security teams with clear reasoning and actionable alerts. Deployment is rapid—under one hour—and the solution is already trusted by U.S. Department of War, intelligence agencies, and critical infrastructure operators.
Target Audience
Primary customers are security operations centers, SOC analysts, and cyber defense teams in government, intelligence, and critical infrastructure sectors that require rapid, autonomous detection of advanced threats across complex or isolated networks.
Features
- Self‑supervised AI that models environment‑specific behavior using dynamical systems, enabling detection of both known and unknown attacks without historical data
- Real‑time threat detection across network layers 2–7, supporting on‑premise, air‑gapped, DDIL, OT, private‑cloud, and AWS deployments
- AI Assistant that triages alerts, prioritizes incidents, and explains each decision to reduce false positives and improve analyst efficiency
- Deep network visibility with multi‑tenant, role‑based access controls for secure data separation in sensitive environments
- Flexible deployment options including portable fly‑away kits for tactical or disconnected networks
- Integrated AI‑powered threat hunting tools that allow manual investigation and automated alert generation for future deviations