This topic examines AI‑powered healthcare agent platforms and the surrounding marketplaces and frameworks used to build, deploy, and operate clinical and patient‑facing agents as of March 18, 2026. Adoption has moved beyond prototypes: providers and payers require enterprise features such as privacy, governance, observability, EHR integration, and human‑in‑the‑loop controls. Key platform types include agent frameworks (LangChain) for engineering stateful, testable agents; no‑code/low‑code visual builders (MindStudio) for rapid design and operationalization; enterprise agent orchestration platforms (Kore.ai) that support multi‑agent workflows with governance and observability; and AI model providers (Mistral AI, Cohere, Google Gemini) offering private, customizable, and multimodal foundation models for clinical reasoning and retrieval‑augmented workflows. Conversation‑intelligence and voice agent vendors (Observe.AI) and document Q&A tools (PDF.ai) address contact center and clinical documentation use cases, while managed hybrid services (Crescendo.ai) combine agentic automation with human experts for outcome guarantees. Current trends emphasize efficient, open foundation models deployable in privacy‑sensitive environments, robust retrieval/embedding pipelines for clinical knowledge, and marketplaces that let teams mix models, tools, and supervised human workflows. Evaluation priorities for healthcare remain accuracy, data locality/compliance, auditability, integration with clinical systems, and clear escalation paths for safety. This comparison synthesizes capabilities across AI agent marketplaces, frameworks, tool marketplaces, and automation platforms to help clinical engineers and procurement teams choose solutions that balance operational readiness, regulatory constraints, and the need for interpretable, observable agent behavior in production healthcare settings.