Security Operations
Embed Agentic Security Platform
Autonomous investigation agents trained on real SOC cases to kill alert noise and false positives.
Embed Agentic Security Platform Overview
What it does
Embed is an agentic security platform founded in 2024 by security practitioners Seth Summersett and Jeffrey Johns, who bring over 50 years of combined experience from Google, Meta, FireEye, Mandiant, and the NSA. Unlike generic AI SOC solutions that rely on off-the-shelf models, Embed's AI agents are purpose-built and trained on actual security investigations, enabling them to reason like expert SOC analysts while maintaining complete transparency into their decision-making process. The platform combines the speed of AI with the precision of human security expertise through proprietary iSteps technology that mirrors expert analyst workflows.
How it works
Embed's core innovation is iSteps, intelligent investigation modules that gather evidence, formulate and answer critical questions, and reason over results exactly as seasoned security professionals do. The platform features NoiseIQ, a dynamic knowledge base with intelligent ingestion that shapes what data moves forward in the pipeline, and Case Assistant, a purpose-built investigation tool that provides case-aware context without requiring analysts to restate endpoints, hashes, or alert IDs. This analyst-centered approach reduces repetitive tasks and enables teams to focus on high-value work like remediation, threat hunting, and learning while continuously adapting to new threats.
Credentials and traction
Embed holds SOC 2 Type II certification and publishes its attestations through a public trust center. The platform is used by security teams including law firm Spencer Fane and the University of Montana, and in April 2026 was selected by a top global IT and security management provider to run high-volume, multi-tenant SOC investigations. Adoption spans the automotive, insurance, legal, and technology sectors, with named customers reporting substantial reductions in analyst investigation hours.
Key Capabilities
mapped to solution categoriesInserts AI-generated analysis, triage decisions, and enrichment into existing SIEM and SOAR case management workflows rather than requiring analysts to use a separate interface.
Assembles chronological attack timelines from raw events across multiple data sources automatically, reducing the time to build an initial incident narrative.
Applies ML classification to incoming alerts to filter false positives, group related events, and route high-confidence detections to analysts, reducing L1 analyst workload.
Accepts natural language queries over security telemetry and translates them to structured queries, enabling investigation without requiring analyst proficiency in SPL, KQL, or SQL.
Suggests the next investigative or containment steps for an alert or incident, with the supporting reasoning, so analysts can confirm and act rather than deciding from raw telemetry alone.
Compliance
certificationsIntegrations
compatible toolsImplementation & support
Info last updated on May 28, 2026
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