This topic covers AI health platforms that prioritize physician oversight and auditable governance—examples include vendor offerings such as ChatGPT Health, DeepHealth, and integrated Clinical AI suites. It explains how these systems combine clinical workflows, enterprise LLMs, and governance layers to deliver decision support, patient communications, and operational automation while keeping clinicians in the loop. Relevance is high in early 2026 because health regulators and providers increasingly require traceability, data residency controls, and explicit clinician review before clinical actions; concurrently, health systems are adopting private LLMs and no-code agent builders to scale safe deployments. Key tool types and examples: enterprise virtual assistants (IBM watsonx Assistant) and productivity-integrated copilots (Microsoft 365 Copilot) that automate documentation and workflows; private, customizable model platforms (Cohere) for health-specific models and embeddings; conversation- and voice-AI platforms (Observe.AI) for contact centers and patient outreach; and no-code agent builders with governance features (Cimba.AI) for rapidly creating auditable clinical agents. Less directly clinical tools such as Gizzmo.ai underscore the broader marketplace of AI services but are not healthcare-focused. When evaluating platforms, prioritize governance and compliance features (audit logs, model provenance, dataset controls), seamless EHR and workflow integration, clinician-in-the-loop gating for clinical decisions, and vendor support for regulatory requirements (HIPAA, FDA pathways, EU AI Act-era obligations). This topic intersects three categories—AI Governance Tools, Regulatory Compliance Tools, and AI Tool Marketplaces—helping health systems compare solutions that balance innovation with clinician oversight and regulatory risk management.