n8n vs Torq

Torq is a purpose-built AI SOC platform, automating the full alert lifecycle. Its SOC Brain provides a context graph that grounds AI decisions, with features like Recall (learning from resolved cases) and Reflex (learning from analyst corrections) to continuously improve accuracy. Natural language remediation via Socrates and HyperAgents for specialized investigations mean analysts can interact conversationally and delegate complex investigations. In contrast, n8n is a general-purpose automation tool with a visual canvas where you can insert JavaScript or Python anywhere, build multi-agent AI workflows with RAG, and access 500+ integrations. n8n offers granular control—re-run single steps, mock data, and trace every agent reasoning step on the canvas. While Torq embeds human approval for every AI action, n8n provides human-in-the-loop guardrails as standard. Torq's advantage lies in its security-specific context and learning; n8n's in its flexibility and transparency for any workflow. Both support audit logs, but Torq's logs are tailored for SOC compliance, whereas n8n offers log streaming to SIEM.

Torq uses a contact-sales model, typical for enterprise security platforms—you pay for scale and AI capabilities, often with custom SLAs. n8n is freemium, with execution-based pricing (not per step), making it accessible for small projects and scaling predictably. n8n can be self-hosted via Docker, eliminating per-execution fees if you manage your own infrastructure, but you lose cloud convenience and support. For a small team, n8n's free tier is attractive; for an enterprise SOC, Torq's ROI comes from reducing MTTR and alert fatigue, justifying its premium. If you're budget-conscious, n8n's transparent model is easier to forecast; Torq's pricing likely includes services and training, so factor that in.