Eureka DevSecOps, a product spin-off from cybersecurity consultancy Forward Security, was created to productize deep security expertise. The platform addresses a core industry challenge: security teams are overwhelmed by a high volume of alerts from various scanning tools, many of which are false positives. The system integrates with tools like Veracode and Semgrep, normalizing their outputs into a unified dashboard.

The platform's intelligence is driven by two key AI components. First, a sophisticated Natural Language Processing (NLP) model automatically maps detected vulnerabilities to the comprehensive OWASP Application Security Verification Standard (ASVS). This provides a consistent framework for risk assessment, a complex multi-class classification task. Second, an advanced false positive filtering pipeline uses a machine learning model to analyze vulnerabilities and distinguish real threats from noise. This model considers vulnerability descriptions, code context, and scanner confidence scores, achieving high accuracy in identifying which alerts can be safely ignored. For example, analysis shows that a model can achieve over 96% accuracy (ROC AUC) in this task, with scanner confidence score being the single most important predictive feature.

To ensure analyst trust, the platform incorporates Explainable AI (XAI), providing natural language justifications for its classifications. The entire system is built on a scalable, multi-tenant Kubernetes architecture designed to meet enterprise banking-level security standards, including capabilities for air-gapped deployments. This allowed Eureka to successfully launch at Web Summit and onboard production customers.