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The Unified Cybersecurity Data Analytics Platform
Advanced analytics and ML help security teams quickly identify threats, providing context to respond effectively both on-premises and in the cloud.
Behind every alert is enriched context: usage baseline, asset changes, and risk ranking, so analysts focus on what matters most.
Unsupervised machine learning continuously identifies and ranks every asset by activity and exposure—no manual configuration needed.
Dynamic risk scoring hones in on the highest-risk indicators, enabling teams to triage quickly while minimizing noise.
How NetWitness Data Analytics Works
What Makes NetWitness Analytics Different
Capability | NetWitness Approach | Traditional Tools |
---|---|---|
Asset Discovery | Passive, patented ML—automatic and complete | Manual, incomplete |
Threat Detection | Contextual, behavioral, exposure-based scoring | Signature or rule-based only |
Risk Scoring | Multi-factor, adaptive peer-group risk | Static, single-factor |
Analyst Experience | Prioritized dashboard, enriched incidents | High noise, manual triage |
Deployment Flexibility | Scalable SaaS, on-prem, and hybrid; plug & play integrations | Often limited, siloed |
Core Module Features
What Sets Us Apart
Continuous assets and behavioral visibility, even as environments change.
Accelerated investigations and incident response with smart prioritization and enrichment.
Seamless integrations with NetWitness SIEM, NDR, SOAR, and third-party security tools.
Scalable analytics platform, process millions of events daily on-premises or in the cloud.
Integrations for Total Security
Plug & play with SIEM, NDR, SOAR, cloud, and endpoint platforms.
Flexible APIs and connectors for easy integration with existing workflows
Expert Insights and Strategies
Proven Results Across Industries
Future-Proof Detection – From Unknown Threats to Rapid Response
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