Fluency vs. Securonix

Why next-gen SOCs are rethinking Securonix. Fluency offers the speed, transparency, and AI execution today's teams demand.

AI Implementation

How Does Securonix's AI Compare to Fluency?

Securonix pioneered User and Entity Behavior Analytics (UEBA), applying machine learning to detect behavioral anomalies. However, their AI is largely focused on detection—not workflow execution.

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Securonix

Securonix pioneered User and Entity Behavior Analytics (UEBA), applying machine learning to detect behavioral anomalies. However, their AI is largely focused on detection—not workflow execution. Alerts still require human follow-up, context gathering, and manual triage.

  • • UEBA models flag anomalies but do not initiate triage or remediation
  • • No evidence of Multi-Context Processing (MCP) or streaming state awareness
  • • Heavy reliance on correlation and scoring—no true AI workflows
  • • Remediation is largely manual, requiring analyst decision-making
  • • AI may enrich alerts but doesn't reduce analyst workload end-to-end
Fluency

Fluency uses AI as a full actor within the SOC. It watches behaviors, links events into timelines, executes playbooks, and closes tickets autonomously. This goes far beyond scoring.

  • • Structured AI workflows: Validate → Scope → Respond → Review
  • • Multi-Context Processing enables memory across event streams
  • • Uses FPL, a JavaScript-based logic engine for dynamic AI behavior
  • • Closes real tickets and modifies posture autonomously
  • • Reduces human workload by solving Tier 1 and Tier 2 problems in-stream

Detection Philosophy

Correlation vs. Real-Time Process

Securonix's strength lies in scoring and correlating events across sources—but this comes with delay, storage overhead, and reactive posture. Fluency instead acts in real time, detecting behaviors as they occur and enforcing response immediately.

Securonix

Securonix's strength lies in scoring and correlating events across sources—but this comes with delay, storage overhead, and reactive posture. Their approach is built around batch processing and risk scoring rather than real-time action.

  • • Batch Behavior: Detections depend on accumulated behavior over time
  • • Black Box Scores: Risk scores are opaque, often lacking explanation
  • • Manual Response: Even flagged alerts need human validation and action
  • • Cloud-Native but Storage-Heavy: Often logs everything before acting
  • • Reactive Posture: Actions taken after threats are identified, not prevented
Fluency

Fluency instead acts in real time, detecting behaviors as they occur and enforcing response immediately. It's built for streaming processing and autonomous action rather than retrospective analysis.

  • • Immediate Detection: Behaviors are recognized and scored live
  • • Explainable Decisions: FPL logic makes every detection traceable
  • • Autonomous Action: AI can triage, respond, and close without analyst review
  • • Stream First: Actions are taken before logs ever hit cold storage
  • • Proactive Posture: Threats are neutralized as they emerge

Direct Comparison

Head-to-Head: Fluency vs Securonix

See how Fluency's AI execution capabilities compare to Securonix's UEBA detection. While Securonix flags anomalies, Fluency acts on them autonomously.

FeatureFluencySecuronix
Detection LogicStreaming-based with real-time AICorrelation + risk scoring
AI ExecutionWorkflow-based with autonomous actionAlerts enriched, but actions manual
RemediationTickets closed by system, posture modifiedAnalyst reviews and acts
TransparencyOpen logic (FPL)Opaque scoring models
Compliance AlignmentISO 42001-AlignedNo visible ISO 42001 structure
AI execution.
Fluency uses AI to execute complete workflows autonomously, while Securonix uses AI primarily for detection and scoring.
Real-time processing.
Fluency processes events as they occur with immediate response, while Securonix relies on batch correlation and delayed action.
Transparent logic.
Fluency uses FPL for clear, explainable automation, while Securonix keeps scoring models opaque and unexplainable.
Autonomous remediation.
Fluency closes tickets and modifies posture automatically, while Securonix requires manual analyst intervention.
Workflow integration.
Fluency structures AI into executable workflows, while Securonix treats AI as a detection enhancement.
Compliance alignment.
Fluency is ISO 42001-aligned for AI governance, while Securonix lacks visible AI compliance structure.

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