Augment SIEM
AI SOC Modernization
Your tools stay. Your detections get sharper. Your SOC workflows accelerate. Automate what slows you down.
The World's Best SOC Teams Use Anvilogic
SOC Modernization for
Detection engineering is essential but painfully slow.
Our 2025 State of Detection Engineering Report reveals that while 80% of organizations are actively investing in detection engineering, only 14% can build and deploy new detection rules in under a week.
Slow Iteration and Complex Custom Integrations
Anvilogic seamlessly supports your existing SIEM and data lakes, with custom detection content and the ability to correlate across platforms.
Painful Migrations and Rule Rewrites
Security teams waste valuable time rewriting outdated rules and rebuilding configurations from scratch. Starting over is not viable, and rip-and-replace migrations are both costly and disruptive.
Alert Fatigue and Scaling Challenges
Overreliance on atomic alerts floods analysts with false positives and drains productivity. Scaling detection expertise—not just analyst capacity—remains one of the most complex challenges for modern SOCs.
Manual SecOps vs. AI SOC
Smarter Detection Engineering Ops
Smarter Detection Engineering Ops
Detection Engineering Lifecycle Management
Takes Days or Weeks...
Concept
Threat Reports
Threat Hunting
Regulations and Compliance
Pentest & Red Team Exercises
Research
Detection Value Analysis
Data Feasibility Analysis
Detection Engineering
Backlog
Build & Validation
Detection Models
Integrations
Delivery
Release Management
Deployment
Optimization
Metrics Gathering & Reporting
Quality Control
Triage & Investigation Updates
Feature & Bug Requests
Performed in Minutes
Prioritize
Threat Intel to Prebuilt Detections
Continuously updated detections organized by threat group, vertical, and domain — enriched with smart AI recommendations curated for your data feeds.
Streamline
Build, Test, Deploy with Detection-as-Code
Build, test, and deploy detections in SPL, KQL, and SQL with version control and open collaboration. Visual builders accelerate workflows while keeping detections flexible and code-ready.
Triage
Automated Response, Reduced Noise
AI-driven triage and investigation support cut false positives, surface context, and lighten analyst fatigue so teams can move from alert to action in minutes.
Scale, Mature & Improve
Continuous Coverage & SOC Maturity
Automate tuning and MITRE coverage reporting with AI insights. Strengthen ROI by scaling detection engineering practices across any SIEM or data lake.


Use proven detection logic to 10x your coverage.
We prioritize detections specific to your environment, aligned with your assets and threat landscape. Our purple team delivers weekly MITRE-mapped content, and our AI engine recommends what to deploy based on your connected data feeds.

Scale detection management across your team with CI/CD principles.
Manage your detection content, authorship, versioning across your stack. Revert back to previous versions, test before deployment all with software development lifecycle principles.

Correlate notable events with EDR, identity, cloud, and other alert sources.
Reimagine atomic alerts across multiple vendors. Correlate Splunk notable events with signals from identity, EDR, and email to chain multi-stage behaviors into complete attack narratives.

Agentic triage that cuts 45% of alert noise, with 98% confidence.
We believe better detection logic means fewer alerts and faster incident response. Our Triage Analyzer agents automatically enrich every alert we generate allowing you faster time priority.

Automate the toil of SIEM maintenance tasks like tuning and data stack plumbing.
Keep integrations and rules actively running and healthy eliminating tedious dependency babysitting with ML generated recommendations and allowlisting fixes.

Track detection maturity with unified MITRE reporting.
Continuously measure technique coverage, maturity, and gaps across your stack. See progress over time, align detections to MITRE ATT&CK, and prioritize where to build next with data-driven confidence.

Case Study
How PayPal Defends & Detects Across the Threat Landscape
As a multi-year Anvilogic customer, PayPal has refined its approach to behavioral detection. Learn how the team builds attack-pattern scenarios, correlates use cases across data domains, and strengthens defenses against the compromise patterns shaping the financial industry.
Hybrid Architecture
Adopt a modern data lake at your own pace
Our SIEM modernization path helps you streamline data integration and analytics by supporting gradual adoption across your existing tools. Easily connect to modern data lakes without rearchitecting your stack.



Ready to start your SIEM modernization journey?
Get started in minutes or talk to our team to build a phased plan for your data lake journey.
Clear, flexible pricing
Pay only for what you use with flexible plans that grow with your data strategy.
View pricing
Fast proof of value
Connect and explore real or synthetic data across platforms in just a few hours, no long setup required.
Try a quickstart

Get the Latest Resources
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Report
2025 State of Detection Engineering Report
The 2025 State of Detection Engineering Report reveals key trends & challenges in detection engineering—from AI adoption to skill gaps and data access.
Watch Now
Solution Guide
How Anvilogic applies
Detection-as-Code in their Framework
Detection-as-Code in their Framework
Understand the current challenges of the detection engineering lifecycle and learn how Anvilogic helps detection engineers use modular components to build, deploy, and manage threat detection logic in a structured, automated, and scalable way.
Read Now
Solution Guide
Streamline Your Detection Engineering
Understand the current challenges of the detection engineering lifecycle and learn how Anvilogic helps detection engineers augment their Splunk or other SIEM deployments to create more accurate detections and hunt more effectively.
Read More