This topic compares the major enterprise GenAI cloud platforms—Google Cloud Vertex AI, AWS Bedrock (with Unicorne tooling), Microsoft Azure OpenAI, and Anthropic—through the lenses of AI data platforms, model marketplaces, governance, and security. By 2025 many organizations run hybrid and multi‑cloud GenAI stacks that combine hosted foundation models, managed marketplaces, and engineering frameworks to support retrieval-augmented generation, fine-tuning, and production agent orchestration. Key supporting tools illustrate how these platforms are used: Anthropic’s Claude family provides conversational and developer assistants for research, writing, code and analysis; IBM watsonx Assistant enables no-code and developer-driven enterprise virtual agents and multi-agent orchestration; LangChain supplies open-source engineering frameworks and orchestration primitives for building, testing and deploying reliable agentic applications; and Cline is an open-source client‑side coding agent for planning, executing and auditing multi-step coding tasks. Together these tools reflect a shift toward composable stacks that combine model marketplaces, vector stores, ingestion pipelines and runtime orchestration. Relevance and timing: enterprises in 2025 are balancing performance, cost, data residency, and regulatory compliance while adopting model marketplaces and governance controls. That raises priorities for audit logging, model provenance, access controls, secure enclaves, and integrated policy enforcement across cloud providers. The comparison emphasizes practical trade-offs—marketplace breadth, integrations with data platforms, MLOps and model governance features—rather than vendor claims, helping teams choose platforms and toolchains that meet security, compliance and operational needs for production GenAI deployments.