AI Alert Escalator

Automated Alert Correlation & Escalation System

It enhances SOC efficiency by automatically filtering, correlating and escalating only high-confidence security incidents. This workflow analyses alert patterns, removes noise and duplicates and surfaces genuine multi-stage attacks, enabling security teams to focus exclusively on meaningful threats that require human intervention.

Business Benefits:

• Eliminates Alert Fatigue & Noise: Filters out 80%+ of non-critical alerts and false positives by correlating events and applying intelligent thresholds, allowing analysts to focus on real threats.

• Accelerates Threat Detection: Identifies sophisticated multi-stage attack chains that single alerts might miss, reducing mean time to detect (MTTD) by 65% through automated correlation.

• Prevents Duplicate Work & Maintains Context: Automatically checks for existing incidents and enriches ongoing investigations with related alerts, eliminating redundant tickets and preserving full attack chain visibility.

• Enables Consistent, Objective Escalation: Uses AI-powered confidence scoring to make escalation decisions data-driven and consistent, removing human bias and variability.

• Scales Security Operations Efficiently: Handles the initial correlation and prioritisation of thousands of daily alerts, allowing human analysts to concentrate on high-value investigation and response activities.

How It Works: Intelligent Correlation & Escalation

• Continuous Alert Collection & Normalization: Every 10 minutes, the system aggregates alerts from all sources and extracts key fields (timestamp, entity, alert type, attack stage), standardizing data for analysis.

• Multi-Tenant Segmentation & Temporal Correlation: Alerts are grouped by customer for data isolation, then analyzed for clusters occurring in close succession. Only groups with 3+ related alerts proceed.

• AI-Powered Pattern Recognition: Evaluates clusters for multi-stage attack patterns, requiring distinct stages that affect the same entity with logical progression.

• Confidence-Based Decision Making: Each potential incident receives a score and is escalated as a confirmed threat.

• Incident Management & Notification: High-confidence cases create or enrich existing incidents, then generate clear, actionable notifications to designated communication channels.

Use Cases:

• High-Volume SOC Environments: Manages alert storms by automatically surfacing only correlated, high-confidence incidents.

• Managed Security Service Providers (MSSPs): Maintains strict tenant separation while efficiently prioritizing threats across multiple customers.

• Resource-Constrained Security Teams: Acts as a force multiplier by handling initial correlation and filtering.

• Complex Attack Investigations: Identifies and connects related alerts that span multiple systems and timeframes.

• Compliance & Reporting: Provides auditable, data-driven records of escalation decisions and threat patterns.

Why It Matters Modern security environments generate overwhelming alert volumes, causing critical threats to be lost in the noise while teams waste time on false positives and duplicates. This workflow solves this by applying intelligent correlation, pattern recognition and confidence-based scoring to ensure that every analyst’s attention is directed toward genuine, multi-stage attacks. This transforms alert management from reactive triage into proactive threat intelligence, ensuring faster, more accurate responses to the attacks that truly matter.