Use case

Splunk Security Operations

Scale SOC analyst capacity using and Splunk

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SOC Analysts are barely keeping up the pace with the volume of incidents.

Splunk provides much needed visibility, detection and automation capabilities; however the shortage of skilled professionals able to handle the volume of incidents that MSSP and Enterprise organizations are facing, as well as fatigue and slow transition to automation are among the biggest challenges of today’s SOCs.

Too many attacks to manage, not enough skilled professionals to handle them and complexity result in burnout, turnover, and lower efficacy than is required.


That’s SOC today and will continue to be until a radically different approach is used: decision intelligence. platform is among the first in introducing decision augmentation for SOC teams, using an innovative method for expert knowledge integration that combines continuous human feedback-loop, Natural Language Processing and deep learning. integrates seamlessly with Splunk Security Operations Suite to scale capacity and increase efficiency of SOC analysts by using AI models created and continuously updated using continuous human feedback-loop, no code.


• Scale SOC analyst capacity to handle security incidents using decision intelligence

• Easily integrate ArcannaAI on top of existing Splunk Security Operations Suite

• Create time for more hunting while avoiding SOC analyst burnout and turnover

• Reduce risk of missing or mishandling a threat due to fatigue

• Retain institutional knowledge

Case study

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