Understand the criteria, evidence, and scoring model behind Fluency’s AI SIEM grades. This methodology explains how we evaluate automation maturity, ISO 42001 alignment, MCP orchestration, and real-world response.
AI grading focuses on how a SIEM operationalizes automation. We look at provable controls—ISO 42001 readiness, adoption of the Model Context Protocol (MCP), workflow orchestration, containment, and roadmap credibility. Vendor marketing often highlights copilots and dashboards; our methodology evaluates architecture, governance, and action.
Each criterion below carries equal weight. Failing any metric means the SIEM still depends on humans to close the loop. Scores are driven by public evidence: documentation, product demos, roadmap disclosures, and direct platform usage where available.
Grades are assigned based on observable capabilities—not roadmap promises. Each table shows what an A through F means for the corresponding criterion.
Evaluates whether the SIEM is aligned with emerging ISO 42001 AI governance controls.
| Grade | Definition |
|---|---|
| A | Actively certified or publicly pursuing ISO 42001 with evidence of controls. |
| B | Partially aligned or structurally prepared for ISO 42001 adoption. |
| C | Roadmap commitment or pilot programs toward ISO 42001. |
| D | Other security certifications (SOC 2, ISO 27001) but no ISO 42001 path. |
| F | No visible ISO 42001 or AI governance initiative. |
Measures support for agent orchestration standards rather than proprietary copilots.
| Grade | Definition |
|---|---|
| A | Published MCP interface with active agent orchestration. |
| B | Implemented but not publicly documented MCP interface. |
| C | Announced MCP support or in-progress integration. |
| D | Custom agent architecture without MCP compatibility. |
| F | No MCP or agent orchestration support. |
Determines whether AI workflows execute end-to-end actions or merely suggest steps.
| Grade | Definition |
|---|---|
| A | AI workflows run autonomously via MCP with analyst approval gates. |
| B | AI workflows run via MCP but still require analyst execution. |
| C | Workflows exist but use proprietary or manual orchestration. |
| D | Stateless AI queries or copilots with no workflow context. |
| F | No GenAI workflow capability. |
Assesses whether AI can stage or execute containment actions automatically.
| Grade | Definition |
|---|---|
| A | AI directly modifies posture (e.g., blocks accounts, rotates keys). |
| B | AI stages remediation actions or closes tickets programmatically. |
| C | AI recommends specific playbooks for analysts to run. |
| D | AI offers general advice or summaries without actionable steps. |
| F | No AI-powered remediation or recommendations. |
Scores public commitment to bringing ISO controls, MCP, workflows, and remediation together.
| Grade | Definition |
|---|---|
| A | Roadmap covers ISO 42001, MCP, workflows, remediation, and feedback loops. |
| B | Roadmap covers four of the above pillars. |
| C | Roadmap covers three of the above pillars. |
| D | Roadmap mentions only one or two pillars. |
| F | No clear AI roadmap or maturity plan. |
Overall grades reflect how well each SIEM delivers autonomous AI operations today, based on the five criteria above.
| Vendor | AI SIEM Grade | Summary |
|---|---|---|
| Fluency SIEM | A | Only SIEM with production MCP supervisors, ISO 42001 controls, autonomous remediation, and documented feedback loops. |
| Microsoft Sentinel | C | Identity progress and strong roadmap, but AI workflows remain assistive and remediation stays SOAR-driven. |
| Securonix EON | B– | UEBA maturity and identity analytics are solid; MCP orchestration and ISO governance are still emerging. |
| CrowdStrike Falcon SIEM | B | Strong automation inside the Falcon ecosystem with identity-driven cases; third-party telemetry still leans on manual playbooks. |
| Splunk Enterprise Security | C– | Copilots and SOAR scripts add assistive AI, yet MCP orchestration, ISO governance, and autonomous remediation are missing. |
| Google Chronicle | C– | Fast search and timeline support; AI remains advisory with no MCP integration or ISO 42001 roadmap. |
Each criterion below illustrates where automation is production-ready, partially implemented, or still reliant on human workflows.
| AI SIEM Criterion | Fluency AI SIEM | Microsoft Sentinel | Securonix EON | CrowdStrike Falcon SIEM | Splunk Enterprise Sec. | Google Chronicle |
|---|---|---|---|---|---|---|
| GenAI Workflow Execution | Chained MCP supervisors run end-to-end investigations. | Copilot suggests queries; analysts still execute workflows. | Automation roadmap exists, but MCP execution remains limited. | Assistive AI inside Falcon; limited cross-ecosystem orchestration. | Playbooks and human triage dominate automation. | AI generates searches but no workflow chaining. |
| ISO 42001 Alignment | Controls, audit trails, and safety policies in place today. | Working toward ISO alignment with public documentation. | Governance program evolving with partial alignment. | No public ISO 42001 roadmap. | No AI safety governance or ISO commitments. | AI assistance without enterprise governance controls. |
| Autonomous Response | Stages and executes containment automatically with approval gates. | SOAR-driven actions require analyst prompts. | Automations exist via integrations but remain analyst-driven. | Automated actions inside Falcon playbooks only. | SOAR executes tasks, yet analysts still approve and coordinate. | Manual response workflows with no automation. |
| Case Narrative Generation | AI writes full case narratives for analyst review. | Copilot summarizes query results but not entire cases. | Summary capabilities emerging with analyst oversight. | Narratives exist inside Falcon; outside data needs manual assembly. | Analysts document cases manually. | No narrative automation or case summaries. |
| Data Routing & Cost Alignment | Inline routing to SIEM, lake, archive, or drop reduces cost. | Routing possible with multiple Azure services. | Supports multiple destinations via services. | Optimized for Falcon destinations with limited external routing. | Indexer-first retention remains expensive. | Data lake routing available but manual. |
| Streaming Data Fabric | Native streaming fabric with filtering, routing, enrichment, and Parquet placement. | Event Hub ingestion lacks filtering, routing, or tier placement. | Traditional connectors and indexing; no streaming fabric. | Operational fabric for Falcon telemetry; routing and filtering still maturing. | Requires Cribl or third-party fabric; native product lacks inline routing. | Lake ingestion only; no inline filtering or streaming placement. |
| Hybrid & Multi-Cloud Deployment | Vendor-agnostic operations across on-prem and cloud environments. | Azure-first architecture with multi-cloud connectors. | Hybrid support via managed services. | Falcon ecosystem dependency limits hybrid coverage. | Hybrid support via Splunk Cloud and on-prem deployments. | Google Cloud dependency for advanced capabilities. |
It is the only platform that documents ISO controls, supervises agents, and executes containment actions today.
Microsoft, Splunk, and Chronicle provide AI summaries and search suggestions, yet humans still assemble cases and trigger response.
CrowdStrike’s identity-driven workflows score well inside Falcon, but third-party telemetry still breaks automation.
Vendors without AI governance plans cannot guarantee safe, repeatable automation in regulated environments.
AI-driven security operations require more than copilots. Fluency is the only SIEM with MCP-supervised workflows, ISO 42001 controls, and automated case closure in production. Other platforms remain assistive: they recommend searches, summarize alerts, or promise future automation.
Use this methodology to pressure-test vendor claims. Ask for evidence of MCP orchestration, AI change control, and ISO compliance. If those are missing, the SOC will still be driven by humans.
