This topic surveys the current landscape of generative chatbots and virtual assistants — from consumer-facing multimodal models to enterprise virtual agents and conversation-intelligence platforms. It covers foundational model families (e.g., Anthropic’s Claude and Google’s Gemini), LLM platform providers (Cohere), enterprise assistant products (IBM watsonx Assistant, Kore.ai, Yellow.ai), productivity-integrated helpers (Notion), and browser/mobile assistants (Minion AI). Relevance in late 2025 comes from wider enterprise deployments, maturation of multimodal and retrieval-augmented approaches, and growing emphasis on governance, observability, and private/customizable models. Organizations are moving beyond single-turn chat to orchestrated multi-agent workflows and integrated assistants that automate CX and EX processes, handle knowledge retrieval, and fit into developer and no-code toolchains. Key tools and roles: Claude (Anthropic) and Google Gemini serve as multimodal conversational model families and developer APIs for research, writing, code, and analysis; Cohere offers enterprise-grade customizable LLMs, embeddings, and retrieval primitives; IBM watsonx Assistant focuses on no-code and developer-driven virtual agents for enterprise automation; Kore.ai and Yellow.ai provide platforms for building, deploying, and orchestrating multi-agent workflows with governance and observability for CX/EX; Notion embeds AI into a unified workspace for knowledge, docs and automations; Minion AI targets in-browser and mobile assistant use cases. Understanding this space requires evaluating model capabilities, integration and deployment options, data privacy and control, and operational features (monitoring, explainability, multi-channel support). Buyers should weigh multimodal capabilities, developer APIs, enterprise governance, and how assistants will connect to internal knowledge and workflows.