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Torq makes AI SOC investigations continuously self-learning

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Torq makes AI SOC investigations continuously self-learning

Torq unveiled Torq SOC Brain, an AI layer for its SOC Platform that learns from historical investigations and analyst decisions to improve incident response. The company claims its approach differs from competitors by reasoning from precedent rather than simply retrieving past cases for language models to process.

Why it matters: Security operations teams and analysts evaluating SOC automation tools should assess whether Torq's continuous learning mechanism reduces investigation time and improves response quality compared to traditional memory-based systems.

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Torq makes AI SOC investigations continuously self-learning

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Torq makes AI SOC investigations continuously self-learning

Torq released Torq SOC Brain, a layer within its artificial intelligence (AI) SOC Platform designed to continuously learn from historical investigations, analyst decisions, and organization-specific security operations. Unlike typical autonomous investigation systems that merely retrieve past cases, the SOC Brain reasons from precedent and adapts to an organization's unique security environment.

Why it matters: Security operations teams evaluating AI-driven investigation tools should consider whether the system genuinely learns from organizational context or simply retrieves cached cases, as this distinction affects response consistency and tuning requirements.

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