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Embed Security lets analysts teach its AI SOC how to investigate

Original title: Embed Security lets analysts teach its AI SOC Platform how to investigate

Help Net Securityby Industry News ()2 min read
Part of a story covered by 2 sourcesEmbed Security adds tools to teach its AI SOC PlatformMerged summary & timeline
AI summary · x-ai/grok-4.7Summaries by Vani AI

Customer iSteps, NoiseIQ Memories and Detection Engineering encode local practice and suggest SIEM detection changes.

Embed Security announced features that let security teams teach its AI SOC Platform how they investigate, what matters in their environment and how to improve detections. Customer-built iSteps turn natural-language investigative steps into agents on Embed’s existing orchestration framework. NoiseIQ Memories adds changing organisational context, and Detection Engineering uses investigation outcomes to recommend changes to customer-authored detections in supported SIEM platforms across endpoint, cloud, email and identity.

Key facts
  • Analysts describe an approach; Embed turns it into an investigation that can run on its own.
  • Detection Engineering reviews investigated alerts and suggests detection improvements.
  • Coverage named for recommendations spans endpoint, cloud, email and identity.
  • CEO Seth Summersett said teams should teach AI rather than build agents.
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From the original article

2 min read at helpnetsecurity.com

Embed Security announced new capabilities that let security teams teach Embed how they investigate, what matters in their environment, and how to improve their detections. With customer-built iSteps, expanded NoiseIQ Memories, and Detection Engineering, organizations can extend Embed’s built-in security expertise with their own knowledge and operating practices.

Help Net Security

By Industry News · helpnetsecurity.com

Read the full article at Help Net Security

A short excerpt; the article and its images belong to the publisher. Summary, key facts and assessment above are AI-written from the article and can be wrong.