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Compare Fluency with the Leading SIEM Platforms

The only AI SIEM built around chained MCP workflows. See how Fluency replaces alert triage with autonomous investigations while legacy SIEMs remain stuck in dashboard mode.

Use this guide to understand where Splunk, Microsoft Sentinel, CrowdStrike, and others stand on ISO 42001 readiness, GenAI execution, and autonomous response compared to Fluency.

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Summary

Fluency is the first SIEM architected around chained MCP workflows, ISO 42001 controls, and GenAI supervisors. Legacy SIEMs still depend on human triage and scripted rules. Use this roadmap to evaluate which platform aligns with autonomous operations.

Fluency AI SIEM

Recommended

NG-SIEM Grade: A — Only SIEM meeting all NG-SIEM criteria natively.

AI Grade: A — Only SIEM with chained MCP supervisors, ISO 42001 controls, and autonomous response.

Pricing

Microsoft Sentinel

NG-SIEM Grade: C — Identity progress is real, yet streaming analytics, case automation, and fabric capabilities lag.

AI Grade: C — Copilot adds search recommendations but no autonomous response or MCP chaining.

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Securonix EON

NG-SIEM Grade: B– — Strong UEBA and identity work, yet lacks streaming architecture and built-in fabric.

AI Grade: C — Strong roadmap, but ISO and GenAI execution are still under construction.

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CrowdStrike Falcon SIEM

NG-SIEM Grade: B — Strong identity and behavior inside Falcon; limited fabric maturity and cross-source streaming.

AI Grade: C– — Good alignment inside Falcon, but no ISO 42001 or open AI governance.

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Splunk Enterprise Security

NG-SIEM Grade: C– — Powerful platform but still search-centric without streaming fabric or case automation.

AI Grade: D — Alert heavy, manual workflows. No MCP or GenAI execution.

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Google Chronicle

NG-SIEM Grade: C– — Lightning-fast lake with flexible schema, yet lacks identity-first workflows and streaming automation.

AI Grade: D– — Traditional SIEM with search workflows; AI remains assistive, not autonomous.

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Why AI-Driven SIEMs Exist

SOC teams drown in alert queues because legacy SIEMs were designed to aggregate logs, not make decisions. Every new rule adds human toil. Every new data source expands cost without improving mean-time-to-containment.

Fluency treats the SIEM as an autonomous workflow engine. Chained MCP supervisors evaluate signals, apply ISO 42001 controls, and write case narratives before analysts ever log in.

“The question is no longer who surfaces the most alerts. It’s who closes the case before the alert ever appears.”

Autonomous response demands inline AI that interprets context, not a chatbot bolted onto a SIEM dashboard. That’s the difference between Fluency and the rest of the field.

Illustration depicting next-generation SIEM evolution

Further Reading

What Makes a Next-Gen SIEM?

Ingress piping, UEBA clustering, AI workflows, and case automation define next-generation SIEM architecture for modern SOCs. Read the full analysis.

Open Blog Article
How to Evaluate an AI SIEM

Use these three control gates first. If a platform fails any of them, it is still an alerting tool—not an autonomous SOC.

1. GenAI Execution

Does the SIEM orchestrate chained AI agents (MCP) or does it merely suggest searches? Automation should escalate or close cases—not recommend queries.

2. ISO 42001 Alignment

Can the platform prove AI safety and governance? Without 42001 controls, AI output is a liability.

3. Autonomous Response

Does the SIEM stage containment actions automatically or does it wait for an analyst? Autonomous SOCs require workflow ownership, not ticket suggestions.

NG-SIEM Architectural Criteria

These six requirements define a true Next-Generation SIEM. If a platform misses one, it remains a traditional alerting tool regardless of branding.

1. Real-Time Streaming Analytics

Telemetry is evaluated the moment it arrives—no scheduled queries, dashboard-triggered correlation, or batch jobs. State is maintained continuously, not reconstructed from a database.

2. Behavioral and Stateful Detection

Detection leans on behavior: seasonality, clustering, first-occurrence analysis, threshold deviation, and state transitions—not piles of static correlation rules.

3. Identity-First Correlation

Every event attaches to a person, device, application, or service. Identity and relationships become the organizing lens for impact and scope.

4. Case-Based Investigation Workflow

Cases assemble themselves automatically as the system accumulates evidence and context. Analysts review, they do not stitch together the narrative.

5. Noise Reduction Through Event Hierarchy

Raw telemetry collapses into signals via scoring, clustering, deduplication, and enrichment so the SIEM explains the environment instead of overwhelming it.

6. Streaming Data Fabric

A streaming data fabric collects telemetry, parses it, filters noise, and routes it to SIEM, lake, or archive tiers—supporting Parquet/object storage and separating analytics from storage cost.

Who We Compared

These are the SIEM platforms most frequently evaluated against Fluency. Each claims AI capabilities—this page shows what’s truly automated and what still leans on humans.

Fluency AI SIEM

Chained MCP supervisors, ISO 42001-aligned controls, and autonomous response pipelines.

Autonomous. Builds cases before analysts log in.

Detailed Analysis

Microsoft Sentinel

Copilot suggests queries but SOC workflows remain manual.

Assistive. AI is advisory, not autonomous.

Detailed Analysis

Securonix EON

Promising roadmap for automation but lacks chained supervisors today.

Emerging. ISO governance still in progress.

Detailed Analysis

CrowdStrike Falcon SIEM

Strong inside Falcon data, limited outside the ecosystem.

Proprietary. No ISO 42001 governance.

Detailed Analysis

Splunk Enterprise Sec.

Rule-centric SIEM with limited automation beyond SOAR playbooks.

Manual. Analysts remain in the loop for every action.

Detailed Analysis

Google Chronicle

Query-focused SIEM built on Google infrastructure.

Assistive. AI generates search prompts only.

Detailed Analysis

Summary of Each Platform

Fluency AI SIEM

Only SIEM with fully autonomous MCP workflows

Fluency executes GenAI investigations, writes case files, and stages containment automatically. Analysts review and approve—not assemble evidence.

Microsoft Sentinel

Assistive AI layered on manual workflows

Copilot suggests KQL queries and summaries. Analysts must pull context and document every step manually.

Securonix EON

Roadmapped automation, limited evidence today

Strong vision but MCP orchestration and ISO controls are still evolving.

CrowdStrike Falcon SIEM

Great for Falcon data, closed elsewhere

Benefits customers already invested in Falcon. Outside the ecosystem, workflows revert to manual triage.

Splunk Enterprise Security

Manual SOC with scriptable automation

Splunk relies on SOAR and human playbooks. No MCP layers, no autonomous case management.

Google Chronicle

Powerful search, human-led response

Chronicle accelerates hunting but does not orchestrate response or AI governance.

Detailed AI Comparison

The full pass/partial/fail breakdown for each AI criterion now lives in our dedicated methodology page.

View AI SIEM Methodology

Key Takeaways

Only Fluency automates the entire case lifecycle — ingestion, investigation, narrative, and response are owned by MCP supervisors.

Legacy SIEMs add AI assistants — but humans still triage alerts, write evidence, and trigger playbooks.

ISO 42001 is emerging as the AI compliance baseline — Fluency meets it today; others remain in roadmap discussions.

Cost control requires routing plus automation — Fluency routes telemetry to the right tier and resolves cases without human toil.

Conclusion

The only way to fix alert fatigue is to remove the alerts. Fluency’s chained MCP workflows, ISO 42001 controls, and autonomous response loops turn the SIEM into an execution layer—not an inbox.

Ready to see autonomous operations?

Replace alert queues with cases that close themselves. See how Fluency automates investigation and response across your existing telemetry.

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Fluency vs Microsoft Sentinel Fluency vs CrowdStrike SIEM Fluency vs Splunk ES