Metano

Metano provides AI runtime security and governance for enterprises adopting AI agents. Its platform helps organizations discover, assess, monitor, and control agents across employee endpoints, internally developed applications, cloud platforms, and embedded SaaS environments. By connecting agents with their identities, tools, data, and actions, Metano gives security teams the context they need to support AI adoption and respond when an agent behaves outside its intended purpose. AI agents are changing how work gets done. They write and execute code, access business systems, retrieve sensitive information, invoke tools, and delegate tasks to other agents. Their capabilities can also change after deployment as teams add skills, packages, integrations, and permissions. For enterprises, the challenge is understanding what these systems can reach and maintaining appropriate controls as their use grows. Traditional security tools provide important pieces of this picture. Endpoint tools record process and file activity, identity systems manage access, and gateways inspect requests. Metano brings these signals together with events generated where agents run, building a connected record of agent activity. This helps teams investigate a complete session, including the identity used, tools invoked, data accessed, and actions taken. The platform begins with discovery. Metano identifies AI agents and their underlying components, including Model Context Protocol servers, skills, tools, plugins, and packages. It also connects agents to the human and non-human identities they use. This deeper inventory helps organizations identify shadow AI, assess access, understand dependencies, and prioritize agents that warrant closer review. Metano extends that visibility into runtime monitoring, threat detection, and containment. Its intelligence layer, Hive, uses a context graph to connect activity across identities, sessions, tools, and data. Detection combines deterministic signals, specialized models, and broader session context to evaluate agent behavior. Security teams can investigate findings with supporting evidence and apply controls where agents operate. Runtime guardrails can be generated from an agent’s specification or developed through observation of its behavior. Teams can begin in audit mode, review proposed controls, and move individual controls into enforcement. This approach helps organizations scale security oversight as agents multiply, while reducing the burden of maintaining separate rules for every workflow. Metano also addresses the growing AI software supply chain. Skills, packages, and third-party tools influence what an agent can do, making their capabilities and dependencies important parts of an enterprise’s security assessment. Metano brings supply chain vetting into the same platform used for discovery and runtime protection. Designed to work alongside existing security investments, Metano integrates with enterprise identity, device management, cloud, and security operations systems. Deployment options include customer-controlled infrastructure for organizations with strict privacy and data sovereignty requirements. Findings include evidence mapped to frameworks such as MITRE ATLAS and the OWASP Agentic Top 10. Founded by enterprise security leaders Neelima Rustagi and Ratnesh Pandey, Metano combines experience building and scaling security products with a focus on the operational challenges of agentic AI. Its goal is to help enterprises put agents to work with clear ownership, appropriate access, observable actions, and controls that keep pace with how those agents actually operate.