Agen Observability

Agen Observability is a platform designed to provide visibility and governance over AI agents, copilots, and Model Context Protocol (MCP) connections that employees have authorized to access company systems. Core function: The platform automatically discovers and catalogs all AI agents, copilots, and MCP connections operating within an organization's environment, including those that were never formally registered or approved. It maps live agent exposure and identifies high-risk access and governance gaps. Key operational areas: - Agent Inventory: Catalogs all AI agents with access to internal tools, enabling organizations to identify and manage unauthorized agentic usage. - User Monitoring: Tracks which employees are using which AI agents, with a focus on preventing personal agents from accessing corporate data. - MCP Observability: Monitors official and unofficial MCP usage to detect unauthorized or homegrown MCP servers that may transmit sensitive data. - Skill Tracking: Tracks which agent skills are active within the organization to prevent malicious or unapproved skills from entering the technology stack. Governance and enforcement: The platform routes agent access through scoped MCP connectors tied to real user identities, replacing ad hoc credentials. It applies role-based access control (RBAC), data masking, and context-aware policies at runtime. It detects rogue agents, unauthorized API calls, and policy bypasses in real time and can block them before data exfiltration occurs. Compliance and audit: The platform maintains a centralized, auditable record of which agent accessed what data, under which policy, and through which connection, supporting compliance reporting and security audits. The platform is positioned as an identity and access infrastructure layer specifically for AI agent governance, addressing the risk of Shadow AI within enterprise environments.