This topic covers the tools, workflows, and governance practices needed to produce licensed‑character and IP‑safe content with generative AI — the “OpenAI‑Disney” style use case where brands, studios, and partners must protect rights, likenesses, and creative control. As of late 2025, organizations are prioritizing private/custom models, rights‑cleared data sources, provenance tracking, and deployment controls to meet legal, brand‑safety, and regulatory requirements. Key tool categories include rights‑cleared data platforms and AI tool marketplaces (for licensed training assets and vetted models), generative image and video tools (for multimodal assets), and enterprise LLM/agent platforms that enable controlled, auditable production workflows. Representative platforms from the market illustrate these roles: Cohere and Google Gemini offer private, customizable LLMs and multimodal APIs for fine‑tuning on licensed material; IBM watsonx Assistant, Kore.ai, and Yellow.ai provide enterprise agent frameworks and multi‑agent orchestration for production workflows and approvals; Claude (Anthropic) is used for conversational and developer‑oriented assistants that can enforce policy constraints; Harvey delivers domain‑specific workflows useful for contract, rights, and legal review; Notion and ThinkForce support collaborative creative workflows, knowledge capture, and handoffs between legal, brand, and creative teams. Successful IP‑safe pipelines combine rights‑cleared datasets, model customization with strict guardrails, provenance/watermarking, human review gates, and marketplace/legal workflows for licensing and revenue share. This topic is timely because heightened regulatory scrutiny, brand risk awareness, and maturing multimodal models now make auditable, contract‑aware generative pipelines a practical requirement rather than an optional capability.