Embed Security lets analysts teach its AI SOC Platform how to investigate
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.
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.
Rather than programming workflows, analysts can teach Embed what they know, and its decision layer applies that expertise autonomously.
Embed’s new Detection Engineering capabilities leverage investigation outcomes to help security teams identify and improve detections across endpoint, cloud, email, and identity.
Customer-built iSteps extend this library, letting teams capture their own investigative expertise as natural-language investigation agents that run on the same orchestration framework.
Analysts describe how they approach a security question, and Embed transforms their expertise into executable investigations that run autonomously when relevant, without requiring customers to program AI workflows.
Our job is to make that expertise executable and apply it consistently across every investigation.
Rather than relying solely on predefined relationships, Embed dynamically connects organizational knowledge with investigative evidence, including context that changes over time.
We think security teams should be teaching AI, not building it, said Seth Summersett, CEO of Embed Security.
Analyzing investigated alerts, Embed provides visibility into detection performance and recommends improvements to customer-authored detections in supported SIEM platforms, giving teams actionable insights and ready-to-apply recommendations.
What happened
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.
Rather than programming workflows, analysts can teach Embed what they know, and its decision layer applies that expertise autonomously.
What changed
Embed’s new Detection Engineering capabilities leverage investigation outcomes to help security teams identify and improve detections across endpoint, cloud, email, and identity.
Who is affected
Customer-built iSteps extend this library, letting teams capture their own investigative expertise as natural-language investigation agents that run on the same orchestration framework.
Analysts describe how they approach a security question, and Embed transforms their expertise into executable investigations that run autonomously when relevant, without requiring customers to program AI workflows.
Response
Our job is to make that expertise executable and apply it consistently across every investigation.
Rather than relying solely on predefined relationships, Embed dynamically connects organizational knowledge with investigative evidence, including context that changes over time.
What security teams should do
We think security teams should be teaching AI, not building it, said Seth Summersett, CEO of Embed Security.
Analyzing investigated alerts, Embed provides visibility into detection performance and recommends improvements to customer-authored detections in supported SIEM platforms, giving teams actionable insights and ready-to-apply recommendations.