AuDRA

Artificial Intelligence
Threat Detection

Built on Deep Neural Net Architecture

Automate the skills, techniques, and expertise of top human analysts to improve threat detection efficacy across your security operations – at machine speeds and machine scale. LogicHub’s advanced artificial intelligence (AI), Autonomous Detection & Response Assistant (AuDRA), and automation mirrors and enhances the cognitive and intuitive approach of expert security analysts and progressively learns and updates its own logic to make more accurate decisions.

LogicHub AI Threat Detection Demo
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What Makes LogicHub AI Threat Detection Unique

LogicHub’s sophisticated artificial intelligence, machine learning, and decision automation helps streamline threat hunting, detection, incident response, alert triage, investigation, and remediation efforts.

What the analysts say about LogicHub:

“LogicHub’s attack detection innovation is “decision automation” ... It enables the skilled hunters to encode their techniques, thus capturing their expertise, and turning it into a scoring playbook and a decision playbook.”

Gartner, Emerging Technologies: Tech Innovators in AI Attack Detection – Demand Side, 2021

How LogicHub AI Threat Detection Works

Our interactive bot-based system, AuDRA, creates playbooks within minutes to hours – instead of days to weeks – and continuously learns from feedback from human analysts and data.

AI decision automation and factor analysis effectively scores risk factors across billions of data points and minimizes noise and false alerts.

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Progressive machine learning algorithms capture input from human expertise, while dynamically establishing baselines for granular anomaly detection.

Learn more about AI Threat Detection 

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LogicHub AI Threat Detection Demo ➔

Watch a demonstration of LogicHub's next generation AI threat detection, AuDRA, in action. 

The Definitive Guide to AI and Automation Powered Detection and Response ➔

Learn why your next SOC assistants are bots (and your networks will be more secure than ever).