Anvilogic has launched agentic workflow automation within its AI Security Operations Center (SOC) platform, enabling autonomous triage, playbook execution, and rapid containment. Announced during the July 2025 technical briefing, the release details how agentic agents conduct detection engineering, alert triage, and response actions using explainable workflows across varied data environments. The update deploys globally for enterprise customers, standardizing automation and reducing manual intervention. The development addresses rising demand for scalable, interoperable, and auditable automation across regulated industries including finance and healthcare.
Background
Anvilogic's platform is powered by an enterprise security graph that classifies incoming data feeds, normalizes event logs, and models entities, relationships, and detection logic across SIEMs and data lakes. This graph supports agentic AI workflows, providing transparency and context-driven automation. The system employs model-context protocols and retrieval-augmented generation (RAG) pipelines to ground agent planning in real enterprise data. Existing agentic agents handle threat intelligence, triage, and detection engineering, with capabilities expanding. The automated framework supports integrations with Snowflake, Databricks, Azure Log Analytics, and Splunk. The enterprise security graph powers automated detection, hunt, and triage built into Anvilogic's platform Agents use RAG, search, and tool calls in LLM-based planning to invoke reasoning or orchestrate across agents Agents integrate via Model Context Protocol and RAG for context-aware automation Agentic AI workflows were already released for detection, hunting and triage, with more capability planned Agentic agents support Snowflake, Databricks, Azure Log Analytics, and Splunk integrations Alarm Fatigue is cut by 45% with 98% confidence in agentic triage workflows The enterprise security graph includes classification and normalization-as-code logic for varied data feeds Agents adapt natural-language inputs like threat reports into operational detections instantly Tuning agents surface query inefficiencies and improve detection code continuously Agentic triage reconstructs alert timelines, enriches context, and triggers SOAR actions with full explainability
Details
Anvilogic's agentic workflows convert natural-language inputs into detection logic and automated triage steps. Analysts supply threat reports or queries in plain language, and agents translate them into environment-specific detections, ready for deployment to SIEM or data lake systems. Normalization-as-code and schema-aware intelligence automate mapping of raw logs into detection-ready formats, streamlining onboarding. The tuning agent monitors detection logic for field mismatches, inefficient joins, and performance bottlenecks. In triage, agents enrich alerts with entity and identity data, prioritize based on threat score and asset criticality, reconstruct alert timelines, and propose investigative queries. They can also invoke downstream SOAR tools while maintaining full explainability. Automated triage, according to Anvilogic, can reduce alert noise by 45% with a 98% confidence rate. Custom agents enable enterprises to integrate their own tools via the Model Context Protocol, while RAG and semantic search keep agent decisions based on real-time enterprise data. All workflows include auditability, governance rules, and standardized playbook compliance to ensure consistency in complex environments. Natural-language inputs become detection-ready logic tailored to each environment Tuning agent flags inefficient detection logic, joined fields, performance issues Agentic triage enriches alerts, prioritizes based on criticality, and invokes SOAR with full explainability Alert noise is cut by 45% with 98% confidence in triage workflows Enterprises can integrate custom tools via the Model Context Protocol in agentic workflows RAG, semantic search, and tool calls support grounded reasoning in agent planning Governance, auditability, and standardized playbooks are embedded across agentic workflows
Outlook
Anvilogic intends to broaden its agentic capabilities to further cover threat hunting, containment automation, and enhancements to detection engineering. As enterprises increase adoption of data lake strategies over legacy SIEMs, requirements for transparent and interoperable automation aligned with governance and regulatory compliance are expected to strengthen. The agentic SOC model may influence SOC staffing, increasingly focusing analyst roles on automation oversight and exception management.
