Anvilogic's Multi-Data Platform SIEM enables enterprise SOC teams to enhance threat detection and investigation by utilizing a low-code detection-as-code builder and AI-driven automation across multiple data sources like Splunk, Azure, and Snowflake. This platform addresses the challenge of detection gaps and high operational costs by streamlining the detection engineering lifecycle and improving alert quality with over 2,100 pre-built detections mapped to the MITRE ATT&CK framework.
Funding
$84.4M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
+1Founders
Product
Problem
Security Operations Center (SOC) teams face challenges in maintaining comprehensive threat detection due to fragmented SIEM data, manual detection engineering processes, and the increasing complexity of modern IT environments. Siloed data across multiple platforms like Splunk, Azure, and Snowflake leads to detection gaps, while reliance on traditional methods slows down the detection lifecycle and increases operational costs.
Solution
Anvilogic offers a Multi-SIEM Detection Platform that streamlines the detection engineering lifecycle and enhances threat detection and response capabilities. The platform decouples the logging platform from security analytics, allowing SOC teams to build and deploy detections across multiple data platforms, including SIEMs and data lakes, without vendor lock-in. By using a low-code detection-as-code builder and AI-driven automation, Anvilogic enables teams to prioritize threats, assess data feed coverage, and quickly eliminate detection gaps. The platform's AI copilot automates detection tuning and maintenance, reducing manual effort and improving alert quality.
Target Audience
Anvilogic is designed for enterprise SOC teams, detection engineers, threat hunters, and security analysts who need to improve threat detection coverage, streamline detection engineering processes, and reduce operational costs across multi-platform environments.
Features
- Low-code detection builder supporting SPL, KQL, and SQL for custom detection development
- AI-powered SecOps Copilot for automated detection tuning and recommendations
- Pre-built threat detection library with over 2,500 detections mapped to the MITRE ATT&CK framework
- Cross-platform correlation capabilities for improved alert quality
- Automated detection lifecycle management for continuous improvement
- Threat prioritization based on business intelligence and threat intelligence
- Dynamic telemetry coverage analysis to identify data sources required for prioritized TTPs
- Agent-led detection coverage mapping to identify gaps in current coverage
- Integrations with existing security tools and data platforms, including Splunk, Snowflake, Microsoft Sentinel, and Databricks