Investigate a meaningful case
Review how UEBA, correlation, clustering, and risk scoring connect activity and prioritize the work. Inspect source evidence behind the conclusion.
Fluency vs Other SIEM Platforms
Compare Fluency against other SIEM platforms in the market. See how our AI-powered approach differs from traditional alert-heavy security models.
AI Implementation
Grading Results
We evaluated leading SIEMs and security platforms against our AI grading criteria. Here's how they stack up.
It's important to note that this is a rapidly evolving space. As vendors race to add AI capabilities, announcements often outpace real-world implementations. Our grading focuses not just on what's promised—but on what's operational, public, and structurally aligned to long-term AI maturity.
| SIEM | ISO 42001 | MCP | GenAI Workflow | AI Remediation | Roadmap | Final Grade |
|---|---|---|---|---|---|---|
| Fluency Security | B | B | B | B | A | B |
| Microsoft Sentinel | B | C | D | C | C | C |
| Securonix EON | F | C | C | C | C | D+ |
| CrowdStrike Falcon SIEM | F | C | D | C | C | D+ |
| Splunk Enterprise Sec. | F | D | F | C | D | D |
| IBM QRadar | F | F | F | C | D | D- |
| Exabeam | D | C | C | D | C | C- |
| Devo | D | D | C | D | D | D+ |
| Hunters | F | D | D | D | D | D |
| LogScale (Humio) | F | F | F | D | D | F |
| Google Chronicle | D | F | D | D | D | D |
| Wiz | D | D | D | F | C | D+ |
Philosophy
SIEM vs Data Lake
Every security tool makes a choice: focus on storing data or acting on it. This comparison shows where key platforms stand.
Fluency
SIEM 90%
Streaming-first SIEM with inline processing and real-time detection.
Elastic
SIEM 20%
Data Lake 80%
Search-focused architecture, strong for log lake use cases.
Splunk
SIEM 60%
Data Lake 40%
Traditional SIEM with indexing flexibility, but increasingly used as a log lake.
CrowdStrike Falcon SIEM
SIEM 45%
Data Lake 55%
Newer SIEM extension to Falcon platform with strong endpoint data, but still maturing on broader ingestion and analytics.
Sentinel
SIEM 55%
Data Lake 45%
Cloud-native Microsoft SIEM with Azure integration and KQL analytics.
Panther
SIEM 30%
Data Lake 70%
Serverless architecture with lake-first design, strong in AWS environments.
QRadar
SIEM 70%
Data Lake 30%
Traditional enterprise SIEM, falling behind in cloud support.
Securonix
SIEM 75%
Data Lake 25%
Cloud-delivered UEBA SIEM with strong ML focus.
Rapid7 InsightIDR
SIEM 65%
Data Lake 35%
Focus on detection and response, supports endpoint integration.
Exabeam
SIEM 70%
Data Lake 30%
Behavior-based SIEM with strong UEBA and modernized cloud push.
Devo
SIEM 40%
Data Lake 60%
Cloud-native log platform with SIEM features and fast backend.
Hunters
SIEM 25%
Data Lake 75%
SIEM alternative using data lake and correlation workflows.
LogScale (Humio)
SIEM 25%
Data Lake 75%
Streaming log analysis with minimal delay, used in modern XDR workflows.
Google Chronicle
Data Lake 90%
Google-scale log lake with detection rules layered on top.
Wiz
Data Lake 90%
Cloud-native platform offering posture and threat detection, not a full SIEM.
🟦 SIEM Focus (Detection, Response)
⬜ Data Lake Focus (Storage, Search)
What to evaluate
Ask for proof across the product and the delivery.
Use the same operational questions when evaluating every SIEM. Fluency brings a strong detection foundation, broad analysis, and hands-on support to that evaluation.
Answer a management question
Compare coverage or health across periods, analyze usage and billing, and review a capacity forecast with its assumptions. Assess certification evidence and gaps.
Establish the deployment path
Review source access, data verification, tenant boundaries, and ongoing support. Test a guided Claude or Codex workflow and inspect the result in Companion.