Whether you build or buy, success begins with the right context.
Every SOC is being asked the same questions: How do we use AI? Where does it fit? Do we build it or buy it? Most answers start with models and agents. But no model can turn stale data, undefined fields, or missing history into ground truth. When context runs short, AI doesn’t stop. It guesses, and it sounds certain doing it.
This Report lays out the context architecture behind defensible security decisions, and explains why internal telemetry and finished threat intelligence alone can’t give your AI the external ground truth it needs.
What you’ll find in the Report:
Key themes from this guide include:
- Build, build around, or buy: Each path to an AI SOC carries different tradeoffs in control, cost, and maintenance. Buying a managed AI SOC doesn’t remove the architecture decisions. It means you bought someone else’s.
- The context stack: Operational knowledge, data semantics, finished intelligence, history, and real-time observation. Learn the five layers that keep AI from inventing the missing pieces, and why a new model can’t fix a field nobody documented.
- Why time matters more than speed: If your AI only knows the current state, it can answer the wrong question perfectly. See why investigations need three views of Internet infrastructure: what’s true now, what was true then, and what changed.
- The hidden economics of autonomous security: AI doesn’t remove the cost of security work. It moves it. Learn why too little context makes AI guess, too much makes it churn, and why you should optimize for cost per defensible decision, not per token, query, or alert.
- One alert, four decisions: Follow a “routine” MFA login from a new IP to a host actively serving credential brute-forcing tooling. Then see how the same Internet evidence drives four different calls across triage, DFIR, CTI, and detection engineering.
Get your copy of Building an AI SOC to learn how to give your AI the evidence it needs, whether you build it, buy it, or both.