Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

The Economics of an Agentic SOC: How AI Reduces Security Operations Costs

See how Torq harnesses AI in your SOC to detect, prioritize, and respond to threats faster. Request a Demo This article was originally published on Security Info Watch. Running a SOC has never been cheap — but in 2026, it’s become unsustainable. The combination of surging alert volumes, rising labor costs, sprawling tool stacks, and skyrocketing breach expenses has pushed the traditional model to the breaking point.

Futureproofing Tines: Fair share orchestration

Fair-share orchestration of resources in a tenant, especially in a multi-tenant context is a complex, multifaceted issue. It involves ensuring equitable access to shared resources, preventing system overload, and maintaining optimal performance across all customer workflows. As more customers build and trust Tines with their most important workflows, (which sees the platform handle over a billion automated actions per week), we recognized that we needed to ensure our platform's scalability.

Voice of Security 2026: AI is everywhere yet manual work persists

AI adoption in security has soared. But for many teams, manual work and burnout remain stubbornly high. To understand why, and what security teams must do next, we partnered with Sapio research to survey more than 1,800 security leaders and practitioners worldwide for our Voice of Security 2026 report. We wanted to learn how teams are using AI and automation, how the role of security is evolving, and how professionals believe AI will impact their careers. The data is revealing.

Context, Memory, and Learning in the AI SOC

Everyone’s chasing a smarter agent. But the model was never what held the SOC back. The sharpest LLM still won’t know your environment, your team’s past calls, or where they draw the line on risk. That lives in the layer beneath the agents: context, memory, and learning. Torq’s AI research team breaks down how we build it.