Complete Network Visibility and Predictive Threat Detection Powered by Autonomous AI
Analyze network traffic, surface threats and anomalies, and stop attacks in real time with the most powerful Context-Aware AI in cybersecurity.
Comprehensive Network Traffic Analysis Powered by the Most Advanced AI in Cybersecurity
Leading Enterprises Trust MixMode
MixMode's Patented Autonomous AI for Cybersecurity
Developed originally for projects at DARPA and the DoD by Dr. Igor Mezic, MixMode AI is true context-aware, third-wave AI that learns unsupervised by human input.
AI Powered Network Traffic Analysis
Baseline Your Network and Start Surfacing Threats in only 7 Days. No Rules or Tuning Needed.
The MixMode Network Traffic Analysis Platform delivers complete network visibility, smarter tools for guided investigation, and real-time threat detection capabilities. Using our patented Third-Wave AI enabled toolkit, your security team can efficiently perform real-time and retrospective threat detection and visualization like never before.
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Learn How MixMode Provides the Most Advanced Multi-Stream Network Security Analytics and Predictive Threat Detection Across Any Data Stream
Intelligent Network Security and Analytics
The MixMode Platform provides operators with full visibility over the network and the tools to perform deep forensic investigations while intelligently monitoring your network's baseline to identify and surface new threats and anomalous activity.
MixMode monitors patterns in your network for odd behavior constantly, alerting users to any abnormality in the pattern of the network baseline allowing users to identifying new threats and Zero-Day Attacks in real time.
MixMode provides users with IDS (leveraging Bro/Zeek), digital forensic investigation capabilities, full packet capture, time travel for playback of events, incident response and more.
Autonomous Self-Tuning Artificial Intelligence
Most Artificial Intelligence in cybersecurity requires human input or “supervised learning” to function. This not only makes the AI vulnerable to hackers who can uncover how the AI was trained, but it also means security teams must wait an average of 18 months before they can obtain value from the AI.
MixMode's third-wave AI, which was originally built for projects at DARPA and the DoD, is hyper-intelligent and can learn about your network, unsupervised and without human input, in less than 7 days.
MixMode studies and creates a baseline of your network by monitoring historic traffic and understanding typical network activity. This allows us to identify potential threats like Zero-Day Exploits, eliminate 90% of false positive security alerts, and cut through the noise to deliver actionable alerts which you can respond to in real-time.
Deep integration with your security stack
In order to identify and take action as quickly as possible when an attack is happening, it's extremely important to ensure full integration across your security toolkit.
Using our robust API, you can seamlessly integrate with your security stack with MixMode by offloading data into SIEMs, orchestration engines and ticketing systems.
We integrate with market-leading tools like Splunk, ServiceNow, LogRhythm, Demisto, ConnectWise, Pager Duty and more.
True Security Threats are Getting Lost in the Noise
Mixmode can help your security team focus on the threats that matter
HighCastle uses MixMode’s PacketSled platform with purpose-built AI to provide continuous risk monitoring to its clients.
The security team for a defense contractor with a national/worldwide presence, selected MixMode as a core tool to increase visibility and significantly improve the IT security defenses that safeguard its networks.
Global Healthcare Exchange, LLC (GHX), has implemented MixMode as a tool to increase security and visibility into its GHX Global Network. Through its cloud-based technology, GHX serves the largest e-commerce community in healthcare, including more than 4,100 healthcare providers globally.
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See How MixMode's Cybersecurity AI Can Help You Start Automating Threat Detection and Response