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Fluency vs. Securonix

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

🤖 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. Alerts still require human follow-up, context gathering, and manual triage. Fluency takes a fundamentally different approach—one rooted in action.

BFluency

CSecuronix

Securonix AI Design Gaps

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: Built for AI Execution

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

📈 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 Limitations

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

Fluency Advantages

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

📊 Head-to-Head Comparison

Feature	Fluency	Securonix
Detection Logic	Streaming-based with real-time AI	Correlation + risk scoring
AI Execution	Workflow-based with autonomous action	Alerts enriched, but actions manual
Remediation	Tickets closed by system, posture modified	Analyst reviews and acts
Transparency	Open logic (FPL)	Opaque scoring models
Compliance Alignment	ISO 42001-Aligned	No visible ISO 42001 structure

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