This topic covers enterprise platforms that address AI governance, model-risk management, regulatory compliance, and ESG/AI disclosure—with a focus on model monitoring, observability, and runtime controls for deployed agents and generative models. As of 2026-01-31, organizations face larger-scale LLM and multi-agent deployments, more frequent real‑time customer interactions, and heightened expectations from regulators, auditors, investors and customers for traceability, safety and measurable impact reporting. That combination makes integrated governance and compliance tooling essential. Key tool categories include AI governance platforms (policy enforcement, access controls, provenance and explainability), regulatory compliance tools (audit trails, reporting and data residency controls), and AI security/governance (runtime monitoring, anomaly detection, and incident response). Examples from the provided tool set illustrate typical capabilities: IBM watsonx Assistant enables enterprise virtual agents with developer and no-code controls for orchestrating assistants; Observe.AI focuses on contact‑center conversation intelligence and real‑time agent assistance with post‑interaction QA and monitoring; Anthropic’s Claude family provides conversational and developer models often integrated into enterprise assistants; StackAI offers no‑code/low‑code end‑to‑end build, deploy and govern capabilities for AI agents; and Kore.ai emphasizes multi‑agent orchestration with observability and governance features. Trends to watch include consolidation of monitoring, explainability and disclosure workflows into platforms; tighter runtime safety and real‑time compliance in high‑risk channels (e.g., voice and customer support); and growing demand for standardized, auditable ESG/AI reporting. Choosing between tools depends on primary use cases—contact‑center monitoring, large-scale agent orchestration, or enterprise-wide model-risk frameworks—and on required integrations with LLM providers, data controls and regulatory reporting pipelines.