Torq is expanding its AI SOC platform with a new product called Agentic Builder, aimed at reducing the engineering work required to build and maintain security automations. Teams want more automation, but building, testing, and tuning those workflows still takes real time and expertise.
Torq's is asking teams to skip the manual work. Instead of having SecOps engineers wire together integrations and logic from scratch, Agentic Builder lets them describe what they want in plain language. The platform then plans the workflow, picks the tools, sets the parameters, and generates AI agents to handle investigation and response tasks. Torq says it also tests those agents against real data before deployment and monitors them in production so they can adjust over time.
Reducing the Engineering Burden Behind Automation
What stands out in this launch is not just automation itself, but who is expected to build and maintain it. Traditional SOAR platforms have already promised automation for years, but they often require dedicated engineering teams to design and maintain playbooks.
Leonid Belkind, CTO of Torq, frames the shift in practical terms. He told MSSP Alert, “Agentic Builder shifts a huge portion of the cognitive load for creating production-grade security automations from humans to the machine. To leverage existing SOAR platforms and their automation playbook model, organizations currently require a dedicated security engineering and automation team. This requirement dictates the high cost and the slow pace of adoption.”
He adds that the impact is measurable in deployment timelines. “Tasks that would typically take weeks or months to complete are now taking minutes or hours… these specific ratios have been proven in Fortune 500 companies.”
The implication is clear. If building automation becomes faster and less dependent on specialized engineering talent, more SOC teams can actually operationalize automation instead of leaving it partially implemented.
What Changes in Day-to-Day SOC Operations
Agentic Builder is designed to take a simple input, a description of a desired security outcome, and translate it into a working workflow or AI agent. That includes selecting integrations, defining guardrails, and structuring the logic needed to investigate or respond to threats.
This changes how work gets done inside the SOC. Instead of backlog-heavy engineering cycles, teams could move closer to on-demand automation, where new use cases are built and deployed as needs emerge.
For organizations dealing with high alert volumes and constant tool sprawl, that shift matters. It can reduce the lag between identifying a recurring problem and putting a consistent response in place. Over time, that could improve response consistency and reduce the operational drag that comes from maintaining fragmented workflows.
How Much Oversight Is Still Required?
One of the immediate questions with any agentic system is governance. If AI is building and running workflows, how much human validation is still needed before those workflows go live?
Belkind suggests the platform is designed to minimize that requirement. “Agentic Builder creates its automation deliverables… not in a vacuum, but on top of this battle-proven platform, reaching production grade does not require any engineering oversight. This is the unique value this generation of technology brings, shifting the cognitive load away from human teams.”
He points to the platform’s accumulated experience as a key factor. “Agentic Builder benefits from the collected experience of how scalable and efficient automations should be built in enterprise environments, as manifested by the components, templates, and building blocks within the Torq AI SOC Platform.”
For buyers, this is where scrutiny will likely increase. The promise of minimal oversight is appealing, but it also raises questions about how organizations validate decisions, enforce policies, and maintain accountability as automation becomes more autonomous.
Where Torq Is Positioning Itself in the Agentic AI Shift
Torq is not alone in introducing agentic AI into security operations. A growing number of vendors are pushing agentic AI into security operations, targeting not just detection and response but the workflows underneath them.
But Torq's argument for differentiation rests on architecture. Rather than building its own agentic capabilities in isolation, the company says it's designed Agentic Builder to plug into AI coding agents developed by the broader software industry. The idea is that as those external agents improve, Agentic Builder improves with them, without Torq having to build everything from scratch.
The bigger picture matters more than any single product launch. SOC automation has long been about helping analysts work through alerts faster. The focus is now moving earlier in the process, toward reducing the effort required to build and maintain the systems doing that work. That's a meaningful shift. If security platforms can generate and manage their own workflows, teams spend less time on upkeep and more time on actual security work.
For SOC leaders, the practical question is how much time their team currently spends maintaining automation. If that overhead is significant, tools like Agentic Builder become less of a nice-to-have and more of an operational lever, one that affects how quickly a team can respond to new threats, absorb new tools, and scale without adding headcount.
