There’s been a lot of buzz lately about using AI to automate Tier 1 and Tier 2 SOC work. Anthropic, using Claude as the base, has been leading with some of the most specific “how to” research. It started with their BSides SF 2025 talk, continued through a run of how-to videos, and lands in their recent eBook Zero Trust for AI Agents, where they lay out how to run defensive operations at the speed of autonomous threats, down to the principle that every inbound alert should get an automated first pass through a triage agent.
In lieu of traditional analysts, Anthropic’s security agents built on the Claude family of models now take the first pass at alert investigations that used to route to a human: pulling in the right data, checking related systems, and taking action within limits that Anthropic set in advance. Every step gets logged, and tricky cases still go to a person. That’s an incredibly successful program. Unfortunately, it’s one that almost no security team has the resources to build in-house.
The good news is they don’t have to. It makes sense that a lab like Anthropic can invest in engineers who can wire an unmodified foundation model into custom tooling, build the memory and context systems that make it useful, and lay down the guardrails and audit trails that make it safe to run, all while having a team of analysts on standby for difficult cases. But this shouldn’t be the standard for every mid-market team looking to build cyber resilience. Arctic Wolf® brings that same speed and automation to security teams everywhere, at a scale no single team could match on its own. And it does it without asking them to take on the years of engineering and heavy infrastructure costs it would otherwise demand.
Here’s how: With the Aurora® Superintelligence Platform and Aurora Agentic SOC, Arctic Wolf runs hundreds of AI agents tuned against real investigations across 10,000+ customers, rather than a single company’s environment. The platform autonomously investigates over 200,000 investigations weekly. This comes from the same category of applied research Anthropic described, run by a team that performs agentic security operations as its core business, not as a side project, and not by bolting a model onto existing tools.
That scale is also how we’re able to bring the world’s largest commercial agentic SOC to organisations that could never fund one on their own. Building this kind of AI engineering once and running it across 10,000+ customers spreads the cost of every model update, every guardrail, and every hour of tuning across the whole Pack, so the bill for any single organisation drops to something a lean security team can actually justify. None of that automation runs unsupervised. Arctic Wolf’s Concierge Security® Team reviews the agentic SOC’s work 24×7, so investigations carry both machine speed and human judgment. That combination is what lets security teams trust the output enough to act on it.
Whether a team builds an agentic SOC in-house, buys it, or blends the two, the goal is the same. Security operations need to move at machine speed while staying accountable to human judgment. The right answer depends on the resourcing and timeline a given team is working with, and that’s a different calculation for a lab investing in its own long-term AI research than it is for a security team that needs coverage now.
If you’re weighing that calculation for your own environment, our ROI calculator lays out the true cost of building this yourself against partnering with us, using your industry, revenue, and user count.
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This blog is provided for informational purposes only. It reflects general industry perspectives and practices and is not intended to represent a guarantee, assurance, or measure of performance. Actual results, outcomes, and capabilities vary by organisation, environment, and implementation.
This post reflects the author’s views as of the publication date and contains forward-looking statements and opinions about technology trends. Actual outcomes may differ based on attacker behavior, customer environments, and broader market and regulatory developments.
