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Gurucul’s Risk Analytics (GRA) offering uses machine learning-based behavioral analytics to help solve security issues.


  • Gurucul is a machine-based behavioral analytics vendor that uses dedicated behavior and risk models combined with out-of-the-box use cases to help organizations fulfil the dream of using advanced analytics to resolve their most pressing security issues.
  • Dynamic peer groups and self-audit functions that are unique to GRA help ensure false positives are reduced and greater context is provided.

Features and Benefits

  • Highlights how customers benefit from out-of-the-box use cases and customization options that maximize the platform’s usefulness.
  • Discusses GRA's ability to work with a customer’s existing big data deployments.

Key questions answered

  • Gurucul Risk Analytics uses machine learning and predictive anomaly detection algorithms to meet its threat, access, and cloud security objectives.
  • Dynamic peer groups and self-audit functions that are unique to GRA help ensure false positives are reduced and greater context is provided.

Table of contents


  • Catalyst
  • Key messages
  • Ovum view

Recommendations for enterprises

  • Why put Gurucul on your radar?


  • Background
  • Current position

Data sheet

  • Key facts


  • On the Radar
  • Further reading
  • Author

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