Security analysts are overwhelmed by the sheer volume and complexity of modern cyber threats. Investigations often require manually piecing together fragmented data across multiple tools, which delays response times and increases the likelihood of missing critical early indicators. Traditional methods struggle to map an end-to-end attack timeline, leaving gaps in understanding adversary behavior and making it harder to prioritize real threats over false positives. This inefficiency drains resources, slows investigations, and limits the SOC’s ability to stay ahead of evolving attacks.
MixMode’s SOC & Analyst Augmentation capabilities leverage self-learning AI to empower analysts with speed, clarity, and actionable intelligence. The platform automatically correlates signals across environments to map complete attack timelines—from subtle early indicators through post-event activity—within minutes. Analysts gain a contextualized view of events, supported by AI-driven insights that highlight root causes, tactics, and potential impact. This augmentation accelerates investigations, reduces analyst fatigue, and enables more informed decision-making, transforming SOC teams from reactive responders into proactive defenders.
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