Agentic AI Security & Governance Tools covers the platforms and controls organizations use to manage autonomous or multi‑agent AI systems with human oversight, auditability, and risk controls. As agentic capabilities move from research prototypes into contact centers, insurance workflows and enterprise automation, teams need centralized policy, runtime monitoring, model provenance, vendor governance, and auditable validation to reduce operational, compliance and safety risk. This topic is timely in 2026 because deployment of autonomous agents at scale has increased regulatory scrutiny, cross‑vendor supply‑chain complexity, and operational incidents that require forensic logging and real‑time mitigation. Key platform categories include no‑code/low‑code agent builders (StackAI, Lindy) for rapid agentization and governance at the application layer; agent orchestration and observability platforms (Kore.ai) that manage multi‑agent workflows and enforcement controls; domain‑specific governance suites (Monitaur, founded 2019, insurance focus) that centralize policy, monitoring, validation and vendor oversight; conversational and contact‑center GenAI platforms (Observe.AI) that combine voice agents, real‑time assist and automated QA; enterprise model and production platforms (Mistral AI) that supply open, efficient models plus privacy‑centric production features; and enterprise virtual assistant stacks (IBM watsonx Assistant) for no‑code and developer‑driven assistant orchestration. Effective governance combines technical controls (runtime guards, observability, automated QA), process controls (policy, vendor risk) and human oversight (review workflows, escalation). Organizations selecting tools should map desired controls to use cases—contact centers, regulated workflows, or cross‑enterprise automation—and prioritize auditability, integration with existing security stacks, and clear vendor governance capabilities.