ExtraHop provides enterprise cyber analytics that deliver security and performance from the inside out. Our breakthrough approach analyzes all network interactions in real time and applies advanced machine learning to help security and IT teams investigate threats, ensure the delivery of critical applications, and protect their investment in the cloud. With ExtraHop, the world's leading enterprises have the complete visibility, real-time detection, and guided investigation they need to rise above the noise and drive their business forward.
Why, Thank You
- Leader in the 2019 Magic Quadrant for NPMD Gartner
- Top 3 Report and Decision Guide for Security Analytics EMA Research
- 2019 Career Launching Companies List Wealthfront
- 2018 Security Industry Innovator SC Media
- 2018 Disruptive Technology Recognition Program Credit Suisse
- 2018 Super 70 List JMP Securities
- 2018 Fortress Cyber Security Award The Business Intelligence Group
- Best AI Solution for CyberSecurity AI Breakthrough Awards
- Best of Show Citrix Synergy 2018
- Sample Vendor in the Hype Cycle for Threat-Facing Technologies Gartner
- Value Leader in Network-Based Security Analytics EMA Research
What The Experts Think
An advantage to interpreting observed network traffic is that SOC analysts can respond to alerts as soon as threats give themselves away instead of struggling to piece together insights from reported log data. Reveal(x) goes a step further in characterizing affected assets by application type and value to the business to help prioritize remediation efforts. It detects threats and delivers correlated, concise investigation guidance built on cloud-based machine learning.
Eric Ogren, Senior Analyst, 451 Research
[Reveal(x)] analyzes all network interactions, applying machine learning to detect abnormal behavior, and then automates basic functions to streamline threat investigations. The launch of Reveal(x) takes ExtraHop into the network detection and response (NDR) market.
Rik Turner, Principal Analyst, Ovum
A complete data source is the starting point for successful security analytics programs. Prioritizing critical assets with insights from smart, machine learning-based network traffic analytics is a way to deliver comprehensive visibility that ultimately enables security teams to sort through the noise of threat alerts in order to detect and investigate what matters most, before critical damage is done.
Rob Bamforth, Independent Analyst