Powered by Sam, the AI SOC Analyst, the Securonix Agentic Mesh delivers governed, explainable AI that measurably improves SOC productivity and enables board-ready outcomes
Securonix, Inc., in collaboration with Amazon Web Services (AWS), today announced Sam, the AI SOC Analyst, and the Securonix Agentic Mesh, introducing a new operating model for security operations designed to scale analyst productivity, govern AI in production, and deliver board-ready outcomes. At a time when security operations are overwhelmed by alert volume, analyst shortages, and rising SIEM costs, Securonix is shifting the conversation from AI features and consumption metrics to measurable work delivered. With Sam and Agentic Mesh, security leaders can now quantify how much analyst work AI completes, govern every AI-assisted action, and communicate impact in operational and business terms.
Sam, the AI SOC Analyst
Sam is Securonix’s AI SOC Analyst. It is a governed, always-on digital teammate that expands SOC capacity without adding headcount. Sam automates Tier 1 and Tier 2 security operations work, including alert triage, investigation, correlation, and response preparation.
Sam operates natively inside the Securonix Unified Defense SIEM and coordinates specialized AI agents through the Agentic Mesh. Human analysts remain in control through built-in human-in-the-loop oversight, ensuring every action is explainable, auditable, and policy-bound.
Sam represents a new unit of value in security operations. Rather than measuring AI by usage or consumption, Sam enables security leaders to measure outcomes in analyst work completed. Each Sam delivers a defined pool of analyst-equivalent productivity, operates under full policy enforcement and human oversight, and reduces alert fatigue by absorbing repetitive work at machine speed.
By pricing AI based on analyst productivity rather than data volume or feature sprawl, Sam enables predictable economics and board-ready ROI narratives.
“By tying AI directly to analyst productivity and governing it by design, Securonix gives security leaders a practical, defensible way to scale operations that stands up to board and regulatory scrutiny.”
– Simon Hunt, Chief Product Officer, Securonix
How Sam Works
Sam orchestrates specialized AI agents across noise reduction, investigation enrichment, response guidance, and reporting, presenting plain-language summaries analysts can review, validate, and act on.
Sam is licensed based on verified analyst-equivalent work performed by AI, with productivity tracked transparently to quantify analyst hours saved and operational throughput gained. By absorbing repetitive Tier 1 and Tier 2 investigative work, Sam allows human analysts to focus on judgment, escalation, and high-risk decision-making without adding headcount.
Agentic Mesh: Governed Orchestration at Scale
Sam operates within the Securonix Agentic Mesh, a governed orchestration layer that coordinates specialized AI agents across detection, investigation, response, and reporting.
Unlike copilots or monolithic AI assistants, Agentic Mesh is designed as a system of work, not a feature. It maintains shared context, enforces enterprise policy, and ensures that every AI-assisted action is explainable, auditable, and reversible.
Built using Amazon Bedrock AgentCore, Agentic Mesh operates securely within the customer environment, providing enterprise-grade isolation, resiliency, and scale.
Turning AI into Governed, Board-Ready Security Operations
Security leaders and boards are no longer asking whether AI is being used in the SOC. They are asking whether it is governed, measurable, and trusted in production. Sam and Agentic Mesh were designed specifically to meet this requirement. Every AI-assisted action operates under policy guardrails, enforces separation of duties, and can be reviewed, approved, or reversed by analysts. AI augments human decision-making rather than replacing it.
The result is a SOC that scales responsibly, maintains regulatory confidence, and produces outcomes leaders can explain to auditors, executives, and the board.
Outcome-Driven Data Economics with DPM Flex
Supporting this productivity-based AI model is Data Pipeline Manager with Flex Consumption (DPM Flex), Securonix’s outcome-driven approach to SIEM data economics.
DPM Flex ensures the right data fuels AI and investigations without runaway SIEM spend by routing telemetry based on analytical value rather than raw volume. This supports predictable economics as environments scale and ensures productivity gains are not offset by rising data costs.
At HDFC Bank, one of the world’s largest financial institutions, Securonix is being used to operationalize agentic AI at scale while maintaining strict regulatory oversight.
“In a regulated financial environment, AI must earn trust through transparency and control,” said Sameer Ratolikar, Chief Information Security Officer at HDFC Bank. “With Securonix, we are using AI agents to reduce noise, accelerate investigations through natural-language search, and prepare response actions, all while keeping our analysts firmly in control. The result is a more productive SOC and clearer visibility into how AI is contributing to real operational outcomes.”
“We built Sam and Agentic Mesh to solve two problems CISOs face every day: unscalable workloads and unprovable AI value,” said Simon Hunt, Chief Product Officer of Securonix. “By tying AI directly to analyst productivity and governing it by design, Securonix gives security leaders a practical, defensible way to scale operations that stands up to board and regulatory scrutiny.”
Sam, the AI SOC Analyst, Agentic Mesh, and Data Pipeline Manager with DPM Flex are available now for Securonix customers worldwide.
