AI SOC Playbook

The Path to Trust in Agentic Investigations

Learn how to move from manual investigations to autonomous case closure at your own pace

Using agents to fix SOC capacity limitations

Alert volume goes up every year. Headcount does not. Every SOC leader knows the compromises that follow: a severity threshold set to what the team can reach, low-priority alerts sitting for days, a backlog that only ever gets resolved by mass-closing it.

AI agents are the obvious answer to a capacity problem, but teams are rightly still hesitant to let agents close cases. No team should expect to flip a switch and have agents start investigating alerts flawlessly.

The AI SOC Playbook is based on the experience of real enterprise teams implementing agentic workflows for SOC investigation, from initial set-up and tuning to agents closing the majority of cases on their own.

the path forward

Six steps to autonomous case closure.

Each step stands on its own and earns the one after it.

1: Clean up detection rules

2: Build familiarity with a co-pilot phase

3: Tune agents to your environment.

4: Enable AI triage with human review

5: Build an agent QA workflow

6: Create deep investigation agents

Free Download

Get the full playbook.

Get the step by step path to agentic investigation your team can run against its own alerts, inlcuding:

  • How to bring agents into your SOC without replacing systems
  • Six steps from manual triage to autonomous case closure, with exit criteria for each
  • The agent corrections that fix most early inaccuracy
  • How to build an audit agent that reopens cases to humans and never closes one
  • A never-auto-close list, a documented stop condition, and the audit package for compliance