This topic covers enterprise-grade multi‑agent and AI agent platforms — the frameworks, marketplaces, and automation systems organizations use to build, orchestrate, deploy, and govern agentic applications. As of 2026, enterprises are moving from single‑assistant deployments to modular, stateful agent architectures that combine domain specialists, developer tools, and product integrations to automate complex workflows while retaining data controls and compliance. Key categories include Agent Frameworks (engineering stacks and stateful runtimes such as LangChain with LangGraph), AI Agent Marketplaces (catalogs of prebuilt agents and templates), AI Tool Marketplaces (integrations and connectors to data, apps, and observability), and AI Automation Platforms (no‑code and developer‑driven orchestration for multi‑agent workflows). Representative products illustrate these roles: LangChain provides open‑source engineering frameworks and stateful orchestration; IBM watsonx Assistant targets enterprise virtual agents and multi‑agent automations with no‑code and developer paths; Anthropic’s Claude family supplies conversational and developer assistants for analysis and drafting; Microsoft 365 Copilot embeds assistant capabilities across productivity apps; Harvey offers domain‑specific assistants for law and professional services; GitHub Copilot focuses on developer productivity and agentic coding workflows; Replit combines an online IDE with Replit Agent and hosting for rapid app shipping. Enterprises evaluating multi‑agent platforms should weigh interoperability, state management, governance, and vendor deployment options (cloud, hybrid, on‑prem). The landscape is pragmatic and modular: frameworks and marketplaces accelerate build cycles, while automation platforms and domain providers deliver packaged workflows—together enabling controlled, auditable agent deployments for production use.