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New-Scale Analytics

ورقة بيانات

Advanced Behavioral Analytics for Human and Digital Identities

What is New-Scale Analytics?

New-Scale Analytics detects threats that hide in normal activity by applying user and entity behavior analytics (UEBA) and Agent Behavior Analytics (ABA) to human users, service accounts, and AI agents.

Security teams face high alert volumes while sophisticated attacks blend into routine behavior. New-Scale Analytics builds behavioral baselines, identifies meaningful deviations, and prioritizes risk using dynamic, multi-layered risk scoring so analysts can focus on credible threats.

How New-Scale Analytics Improves Threat Detection

New-Scale Analytics uses a unified behavioral model to analyze activity across users, machine identities, and AI agents.

Exabeam Nova AI agents accelerate detection and investigation by enabling:

  • Natural-language search with the Exabeam Nova Search Agent
  • Automated triage with incident timelines and detection grouping
  • Dynamic risk scoring based on behavior and context

This approach surfaces insider threats, credential misuse, and AI agent activity earlier while reducing time spent on manual analysis.

How It Supports Security Leaders

The Exabeam Nova Advisor Agent in Outcomes Navigator translates operational data into measurable insights.

Security teams can benchmark performance against:

  • MITRE ATT&CK® techniques
  • Strategic use cases
  • Industry peers
  • Compliance frameworks
  • OWASP Agentic Top 10

These insights help identify gaps, track progress, and communicate outcomes to leadership.

Built to Extend Your SIEM

Built on New-Scale Fusion, New-Scale Analytics layers behavioral analytics onto your existing SIEM or data lake without replacement. It strengthens detection for insider threats, credential misuse, and AI agent activity while providing a unified behavioral view across human and digital identities.

Download the data sheet to see how New Scale Analytics helps security teams detect threats earlier and prioritize real risk.