Autonomous Alert Triage & SOC Noise Reduction

Why You Should Care

• Low-Confidence Queues: SOC teams are overwhelmed by alerts that lack the evidence needed to take immediate action.
• Contextual Blindness: Most alerts arrive without exploitability data, ownership info, or business impact context.
• The "Spelunking" Tax: Analysts spend 80% of their time manually reconstructing a story across siloed tools.
• Operational Inconsistency: Response quality varies wildly based on shift timing and individual analyst experience.

How Tuskira Solves It‍

Tuskira treats the SOC as the last mile, not the starting point. Before any alert reaches an analyst, AI agents validate whether it represents real risk.

• Pre-SOC Validation: This is not playbook automation. Instead of executing predefined steps, Tuskira’s AI agents use the Security Mesh and Digital Twin to determine whether an alert leads to a real, reachable attack path, factoring in identities, permissions, and active controls, before a human is ever engaged.
• Confidence-Based Escalation: Tuskira autonomously closes benign or "blocked" alerts. Only high-confidence threats with verified exploitability reach the human queue.
• Assisted Execution: When an alert is escalated, it comes with a "Decision-Ready Report." AI Agents provide the whole timeline, evidence of impact, and a recommended response, allowing humans to supervise the strategy rather than the search.

Who benefits

• SOC Analysts (Tier 1–3) who need decision-ready alerts, not raw signals
• SOC Managers accountable for alert quality and response consistency‍
• Detection Engineering teams improving signal fidelity over time