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Machine Learning

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Automated Case Prioritization

Siemplify continuously analyzes and prioritizes your case queue to ensure analysts address critical cases first. Using machine learning, Siemplify assigns higher priority to cases that resemble ones historically deemed malicious and assigns a lower priority to cases that resemble ones that have been flagged as false positives.

Assignment Recommendations

Assigning the best suited analyst to a case can make a world of a difference. Siemplify makes this decision easier by combining machine learning from previous analyst performance to make instant case assignment recommendations. Following these recommendations ensures analyst productivity and effectiveness are maxed.

Similar case identification

Attacks are constant but not necessarily unique. Understanding this fact, Siemplify machine learning provides a list of similar cases that analysts can use to aid their current investigation. With easy access to previously resolved similar cases, analysts can see the steps taken in the past to inform the response actions they may take for their active investigation.

Case Tagging

Siemplify makes tagging cases simple by providing recommendations based on previously investigated cases. This capability helps analysts properly categorize their cases and if and when they need to search through case history, they can use these tags to home in on the specific type of case they are researching, saving valuable time.

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