AI SIEM for the Autonomous SOC
Consistent, accurate detection — 24/7, without analyst fatigue.
By applying AI workflows directly to investigation and triage, Fluency delivers results with greater consistency and accuracy — even in the middle of the night when human teams are offline. That means higher-quality detection and response without expanding headcount.
Complete SIEM Architecture
Fluency's SIEM is built on five core components that work together to deliver real-time security operations.
- Streaming Pipes
Ingest, parse, and normalize data from any source in real time. Fluency's streaming architecture processes data as it arrives, eliminating the delays and costs associated with traditional batch processing.
Supports all major log formats, cloud services, firewalls, identity providers, and endpoint detection tools. Data is normalized and enriched immediately upon ingestion.
- Streaming Analytics
Real-time detection engine that evaluates security events as they flow through the system. No waiting for data to be indexed or stored—threats are identified instantly.
Built for streaming evaluation, not retrospective queries. Logic executes inline, providing immediate detection and response capabilities.
- Behavioral Analytics
Tracks user and entity behavior patterns to detect anomalies and unknown threats. Unlike signature-based systems, behavioral analytics identify threats through pattern analysis and deviation detection.
Process-aware architecture links events into behavioral chains with memory, enabling detection of sophisticated attacks that evade traditional rule-based systems.
- UEBA Case Creation and Management
Automatically creates and manages security cases based on behavioral anomalies and threat detections. Each case includes full context, timeline, and recommended response actions.
Integrated case management system that tracks investigations from initial detection through resolution, with automatic updates and status tracking.
- AI Workflows for Analysis
Structured AI workflows that validate, scope, respond, and review security incidents autonomously. Reduces analyst workload by handling Tier 1 and Tier 2 problems in-stream.
Multi-stage workflows powered by FPL (Fluency Process Language) enable clear, explainable automation with real-world context. AI can close tickets and update security posture automatically.
Explore AI Workflows
Defining Next-Generation
What Makes a Next-Gen SIEM?
The technology for SIEM continues to evolve at a rapid pace. What defines a true next-generation SIEM today? Four essential capabilities that separate modern platforms from legacy systems.
The Four Pillars of Next-Gen SIEM
These capabilities aren't just features—they're fundamental architectural requirements. A SIEM that lacks any of these four pillars cannot truly claim to be next-generation, regardless of marketing claims.
Fluency SIEM implements all four capabilities today, built into the core architecture from the ground up. This isn't about bolting on new features—it's about designing a system that keeps pace with modern security challenges.
- Ingress Piping
More than just data collection, ingress piping is the traffic controller for data entering the SIEM. It guarantees delivery, normalizes and transforms events, routes flexibly to multiple destinations, and scales cleanly without dropping packets during spikes.
Without robust ingress piping, a SIEM cannot credibly call itself next-generation. It's the foundation that enables everything else.
- UEBA Clustering
True UEBA combines identity clustering (tracking all actions tied to an actor) with behavioral analytics (stateful analysis that compares current behavior to normal patterns).
Together, these create Identity Behavioral Analytics (IBA)—the cornerstone of next-gen detection that enables case-level analysis.
- AI Workflows
True AI workflows replace the analyst, not the process. They don't assist—they execute structured workflows autonomously, handling validation, scoping, and response at scale.
With AI workflows, alert fatigue fades away. Processing power can be applied without limit, ensuring every event is handled with the same rigor at 2 AM as at 2 PM.
- Case and Response Management
Cases should be built around identities or clusters of related identities, not individual alerts. This dramatically reduces ticket volume and enables lifecycle tracking across related events.
With proper identity normalization, alerts from different systems can be clustered into the same case, providing vendor-agnostic consolidation across the environment.
AI Workflows for Analysis
Fluency's AI-powered workflows automatically detect, investigate, and respond to security threats. Each workflow is designed to handle specific attack patterns and provide contextual analysis that traditional SIEMs cannot match.
Understanding Workflows
Learn how Fluency's AI-driven workflows detect and respond to security threats.
Impossible Travel
Detect logins from geographically distant locations indicating credential compromise.
Email Rule Change
Monitor suspicious email forwarding and filtering rules used in BEC attacks.
New User
Detect suspicious new user account creation and privilege escalation attempts.
PowerShell Analysis
Monitor and analyze PowerShell execution patterns for malicious activity and privilege escalation.
Unknown File Reputation
Analyze file execution patterns and reputation to detect malware and suspicious files.
Lateral Movement
Detect and analyze lateral movement patterns across your network infrastructure.