Watch the video

See inside the mind of a virtual analyst.

Watch

Get our latest white paper.

Learn more about the technology powering our revolutionary platform.

Download Now

Improves detection rates 10x
Reduces false positives 5x*

MIT and PatternEx Researchers did a controlled experiment to see if an AI solution could demonstrate active learning using Active Contextual Modeling.

Active Contextual Modeling (ACM) is a real-time closed-loop Artificial Intelligence system that combines the Analyst’s Intuition with machine intelligence to predict threats.

How it works...

  • Using real world data containing labeled attacks, we compared the detective precision of ACM versus Anomaly Detection approaches.
  • ACM's ability to detect attacks was 10x better than UBA anomaly detection solutions
  • ACM's precision was possible with 5x fewer alerts than anomaly detection solutions

Learn More

(* compared against anomaly detection solutions)

artificial intelligence for cyber security

Read how PatternEx multiplies the efforts of human security analysts

How IOT Security Can Benefit from Machine Learning
AI Can Help Predict Cyber Attacks
AI's Ultimate Challenge?  Cyber Attacks.
Using AI to Multiply Efforts of Human Infosec Analysts
MIT's New AI May Help Prevent Cyber Attacks

Our Blog

News

The PatternEx Threat Prediction Platform

PatternEx Threat Prediction Platform Architecture

PatternEx dynamically extracts user feedback, creating predictive models that continuously adapt to detect both new and existing threats. Learn more about the technology powering our revolutionary platform.

Download Now