This topic covers clinical AI platforms and supporting tools used to build, validate, deploy, and govern AI in healthcare with a focus on regulatory compliance, clinical documentation, AI governance, and security. As of 2025, regulators and health systems emphasize documented model validation, explainability, data residency, audit trails, and human-in-the-loop controls; organizations therefore combine governance platforms with operational assistants and document intelligence to meet those requirements. Key categories include Regulatory Compliance Tools (for validation, evidence collection, and policy management), Clinical Documentation Tools (for charting automation and real-time clinician assist), AI Governance Tools (for model inventory, risk assessment, and red‑teaming), and AI Security Governance (for threat modeling, access controls, and remediation). Representative tools: Cranium — enterprise AI governance and security for discovery, red‑teaming, and remediation; Microsoft 365 Copilot — productivity and document-assist across clinical and administrative workflows; Observe.AI — conversation-intelligence and GenAI for contact centers providing voice agents, real-time assist, and automated QA; Dashworks — omni-search assistant that unifies apps and data for rapid answers; PDF.ai and ChatPDF — document-chat tools for rapid review, summaries, and cited extracts of policies, literature, and consent forms; Notion — an AI-enabled workspace for SOPs, knowledge bases, and audit documentation. Together these tools support an operational stack that addresses model risk management, clinical usability, and compliance evidence generation. Practical deployments prioritize transparent logging, EHR integration patterns, clinician oversight, patient-data minimization, and routine red‑teaming and remediation to satisfy current regulatory expectations without disrupting care delivery.