SIEM

Redefining SecOps for the AI era.

SIEM unifies telemetry, threat intelligence, and risk-based detection into a command layer for organizations that must keep security visibility under sovereign control.

SIEMFigma source 395:3484
SIEM operational dashboard extracted from the source Figma file.
Telemetry Pipeline

Unified data and intelligence pipeline.

Collect logs, files, API signals, and cloud events into a normalized intelligence layer without exposing unapproved performance claims.

Heterogeneous telemetry intake

Organizes file, log, API, and cloud-platform inputs into a common operating picture.

Normalization logic

Uses parser, location, pattern, and evaluation logic to turn raw telemetry into usable intelligence.

Standardized threat context

Aligns detection, investigation, and response teams around consistent intelligence semantics.

Cloud and platform integration

Source material names Huawei Cloud, Azure, and Kafka as integration directions for bringing platform telemetry into the same pipeline.

Analysis Engine

High-concurrency analytics for long-horizon investigation.

The source material highlights a proprietary high-concurrency architecture and UQL hunting layer. Public copy keeps the architecture and workflow detail while withholding unapproved throughput and latency metrics.

UQL search and hunting

Gives analysts a flexible language for deep search logic, investigation pivots, and operational dashboards.

Custom visual dashboards

Turns investigation logic into command views that can be adapted for SecOps, hunting, and executive review.

Long-horizon traceability

Supports historical investigation patterns without publishing the source file's unapproved performance thresholds.

Advanced Detection

Risk-based detection that makes alert pressure operational.

SIEM combines UQL-driven detection rules with Risk-Based Analysis scoring so fragmented events can be evaluated as a coherent risk picture.

Risk-Based Advanced Detection

Frames detection outcomes around risk scoring rather than isolated alert volume.

UQL-driven detection rules

Lets teams express detection logic in the same investigation language used for hunting and review.

Alert consolidation

Connects related signals into a prioritized operating queue for critical-threat review.

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