Levo Runtime Application Security is a platform designed to provide security for API-first and AI-native applications. The product operates at runtime to address security challenges in dynamic application environments where traditional perimeter-based security approaches are insufficient. The platform captures authentication scopes, identities, and data flows across APIs and AI assets to provide context-rich security analysis. It creates a unified runtime graph that connects APIs, agents, LLMs, and MCP servers to enable end-to-end governance of workflows, chains, and recursive calls. Levo integrates data from multiple sources including SAST/SCA tools, code repositories, logs, traffic, infrastructure, and Kubernetes environments. The platform processes this information to deliver security posture assessments, reproducible values, actionable findings, remediation actions, and AI-driven fixes. The product uses eBPF technology for data collection and is designed to integrate into CI/CD pipelines and runtime observability systems. It employs a data processing engine that captures, samples, and processes minimal data to maintain efficiency. Levo addresses security requirements for machine-to-machine traffic, API sprawl, API keys, agentic identities, and prompt/payload exploits that traditional code-centric defenses and edge filters may not adequately protect against.