Anvilogic

Key Features

• Multi-Cloud and Hybrid Threat Detection Support
  Anvilogic is built to support threat detection across hybrid and multi-cloud environments, including on-premises infrastructure. It normalizes data from various sources and applies consistent detection logic across cloud platforms like AWS, Azure, and GCP, offering unified visibility and detection efficacy across distributed environments.

• Machine Learning-Based Threat Detection Models
  The platform uses machine learning to improve threat detection accuracy and reduce false positives. By analyzing past behaviors, anomalies, and contextual signals, Anvilogic trains models that detect threats even when traditional rule-based systems fall short, significantly enhancing the speed and reliability of incident identification.

• Content-Agnostic Detection Engineering
  Anvilogic offers a no-code, content-agnostic interface for building and managing detection logic. This enables security teams to create and deploy detection use cases quickly without being locked into specific vendor formats or writing complex code. It supports SQL, Sigma, and native SIEM query languages.

• Security Operations Center (SOC) Automation Tools
  The platform automates repetitive SOC tasks like alert triage, correlation, and enrichment. These automated playbooks help security analysts focus on high-priority threats while reducing operational fatigue and manual workloads that often hinder SOC efficiency.

• Detection-as-Code and Version Control
  Anvilogic applies modern software engineering practices to detection logic through its “Detection-as-Code” model. This allows for collaborative development, versioning, rollback, and testing of detection rules, enabling agility and governance in threat detection strategies.

• MITRE ATT&CK Coverage Mapping
  The tool includes detailed mapping of detection rules to the MITRE ATT&CK framework, offering transparency and gap analysis. Teams can quickly assess which attack techniques are covered, prioritize threat coverage, and ensure alignment with industry-standard threat models.

Key Benefits

• Improves Threat Detection Across Environments
  Anvilogic empowers security teams to detect threats across hybrid and multi-cloud environments with a consistent, unified approach. It breaks down silos between different infrastructures, enabling more reliable and comprehensive security coverage without duplicating efforts.

• Reduces Alert Fatigue with ML-Powered Precision
  By applying machine learning to alert generation, Anvilogic significantly cuts down on noise and false positives. This precision allows security analysts to spend more time on critical investigations, enhancing their focus and decision-making quality.

• Accelerates Detection Engineering Cycles
  With its no-code interface and support for multiple query languages, Anvilogic enables faster creation and deployment of detection logic. This agility shortens the development lifecycle for new use cases and improves time-to-response during evolving threats or compliance changes.

• Increases SOC Efficiency and Automation
  Automation of triage, correlation, and contextual enrichment helps streamline SOC workflows and reduce manual overhead. This improves response times, allows teams to scale operations without increasing headcount, and helps organizations better utilize their existing security staff.

• Supports Governance and Collaboration in Rule Management
  With Detection-as-Code, Anvilogic facilitates structured collaboration among detection engineers, security architects, and compliance teams. This improves governance, auditability, and repeatability in managing detection rules and responding to threats.

Pricing Plans

• Custom Enterprise Pricing
  Anvilogic operates on a custom pricing model tailored to each organization’s security architecture, size of data ingestion, number of detection rules, and level of automation required. Interested customers must contact the sales team to receive a personalized quote.

• Modular Licensing Based on Usage and Features
  Pricing is typically structured around selected modules (e.g., detection engineering, threat correlation, automation), number of data sources, and usage volume. The modular approach enables organizations to scale and pay only for the functionalities they need.

Pros and Cons

Pros:

• Supports hybrid and multi-cloud threat detection out of the box

• Machine learning reduces false positives and improves detection quality

• No-code detection engineering accelerates development and deployment

• SOC automation streamlines operations and reduces analyst workload

• Detection-as-Code enhances collaboration, version control, and governance

Cons:

• Lacks transparent, self-service pricing information

• May require onboarding support for integration with complex environments

• Designed primarily for mid-to-large enterprise SOCs, less suited for smaller teams

• Some advanced automation features require tuning and SOC maturity to fully benefit

Conclusion

Anvilogic is a robust, enterprise-grade AI platform for threat detection and SOC automation that bridges the gap between traditional detection systems and modern, hybrid infrastructure. Its use of machine learning for alert precision, no-code engineering interface, and automation-driven SOC capabilities make it a valuable asset for security teams operating in complex environments. While the lack of public pricing and its enterprise-focused orientation may limit accessibility for smaller organizations, Anvilogic excels in delivering scalable, intelligent, and collaborative threat detection workflows. It’s an effective solution for organizations looking to modernize their SOC operations and proactively defend against evolving threats.