AI group collaboration platforms bring together threaded team chat, shared context and model-backed assistants to support real‑time collaboration, meeting workflows and knowledge work. As of 2025, this space splits into conversational-first offerings (e.g., ChatGPT Group Chat), multi‑model marketplaces (e.g., Poe) and purpose-built enterprise tools that combine retrieval-augmented generation (RAG), integrations and governance. Demand for on‑prem options, persona memory, multi‑LLM routing and tighter app/search integration is driving innovation. Key players illustrate common patterns: ChatGPT Group Chat emphasizes integrated shared context and OpenAI model capabilities for synchronous team exchanges; Poe provides a marketplace-style experience for trying and switching between different models and assistants. Notion demonstrates how an AI-enabled workspace embeds AI into docs, knowledge and automation; Dashworks focuses on omni-search across apps and data to answer team questions in real time. Lindy lowers the barrier to build and deploy autonomous agents with no/low‑code tooling, while Yellow.ai targets enterprise CX/EX with agentic automation across channels. Specialist platforms like Mindlogic (FactChat) stress RAG, multi‑LLM integration and on‑premise deployment for compliance, and PandaChat offers multichannel assistants that link chat, email and social with contextual knowledge. For teams choosing between ChatGPT Group Chat, Poe and alternatives, the practical differences are choice of underlying models, support for RAG and memory, integration depth with workflows and security/governance options. The current trend favors interoperable stacks that combine marketplace flexibility, workspace integration, agent automation and enterprise controls—making selection a balance of collaboration UX, model governance and systems integration.