EverInsight

Advanced User Behavior Analytics

Respond to Risk With Unrivalled Insight.

Detect, Analyze, Protect with User Behavior Insights

Your employees are your greatest asset, and your greatest risk. Leverage structured and unstructured data to gain unparalleled insight into patterns, activities, and trends that could lead to compromise.

EverInsight provides powerful behavioral insights to analysts so they can rapidly respond to risky behaviors before it’s too late.

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Human-Centric, Risk-Responsive Protection
Maintain an ideal balance of security and productivity with a system designed to respond to behaviors in near real time.
Unparalleled Visibility into Indicators of Compromise
Uncover hidden insights into events known to indicate risky behaviors and automate remediation actions to intervene before a security incident occurs.
Privacy and Integrity by Design
Leverage built-in governance to maintain the integrity of investigations and maintain employee privacy with Do Not Collect policies.

Advantages of User Behavior Analytics (UBA)

EverInsight provides analysts with the ability to define custom policies and risk-responsive rulesets to protect their organization from insider risk. Gain actionable intelligence to protect your organization, streamline operations and make informed decisions based on user behavior patterns.

Why EverInsight?

EverInsight is a powerful user behavioral analytics solution designed to protect not just the organization, but also the innocent. Easily configure policies to detect employee harassment, illegal activities, and compromised users.

Gain a holistic understanding of the highest risk users and define risk-responsive policies to address behavior that can lead to compromise.

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Enhancing Transparency with User Behavior Analytics for Proactive Security

The analytics in EverInsight user behavior analytics are simple and easy to understand, producing accurate and insightful results.
Unlike competitor products, EverInsight provides transparency by exposing enhanced detail so analysts can understand how the user community operates and then add their own expertise to the features and models.
For example, an analytics administrator can change the scoring weight of a cloud storage upload or weekend activity based upon the data feeds from various data sources, such as the organization’s SIEM or DLP tool set.
When the analyst investigates a user of interest, they do so through the user-friendly entity timeline, which provides analytic explanations and context, allowing the analyst to make informed judgments and take appropriate actions as they assess possible security threats.

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