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Applying Agentic AI to Security Operations:

Transparent and Autonomous AI for Faster Response

Eliminate Time-Intensive Tier 1 and Tier 2 Activities

There’s nothing more important in security operations than speed. Containing threats within minutes—not hours or days—is the new standard.

To help organizations combat threats and move faster, ReliaQuest has built an AI Agent within its GreyMatter technology that empowers security teams to respond
even more quickly and efficiently without sacrificing visibility.

It effectively gives customers the ability to train their own self-learning AI Agent on their own environment. This whitepaper highlights:

  • Core components of the ReliaQuest AI Agent
  • How ReliaQuest GreyMatter is uniquely positioned to deliver AI-driven security operations
  • Example incident response workflows taken by the AI Agent

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Leveraging Agentic AI

Agentic AI refers to autonomous AI systems that act independently, making decisions and taking actions without constant human intervention. These systems set goals, optimize processes, and solve problems by analyzing data, learning from experience, and adapting to changing conditions. Agentic AI enhances security operations with faster, more accurate, and scalable threat detection, containment, investigation, and response, while making autonomous decisions and recommendations.

With the ReliaQuest GreyMatter AI Agent , Security Teams Can:

Leverage the AI Models Best Suited to Each Task

Build Trust in AI Models Through Transparency and Accuracy

Reduce Time-Intensive Tier 1 and Tier 2 Activities

The ReliaQuest AI Agent Workflow

AI agents perform complex tasks that require reasoning, reflection, and action. The ReliaQuest AI Agent follows a meticulously designed workflow that ensures accuracy, consistency, and transparency at every stage of the TDIR process.

Planner

Builds the right plan based on alert artifacts, customer environment information, and past alert triage. It creates a series of steps, including:

  • Calling Tools
  • Reflecting Tool Outputs
  • Making Decisions Based on Gathered Data

Tool Selection

The planner chooses tools based on the task requirements. For example, if the task involves detecting impossible travel, the planner might:

  • Use an External Search Tool to Pull Login Data
  • Analyze the Login Data to Identify Unusual Patterns.
  • Reach Out to the User for Verification

Executor

The executor implements the plan, utilizing the appropriate tools for each step. It is capable of:

  • Observing and Requesting a New Plan If a Tool Fails to Return Data
  • Automatically Replanning Around Failures, Including Those That May Occur from Missing or Unavailable Data