This topic covers platforms, frameworks, and marketplaces used to design, orchestrate and operate AI agents in enterprise workflows. It focuses on four categories—AI automation platforms, AI agent marketplaces, agent frameworks, and low‑code workflow platforms—and why organizations are moving from single-model prompts to multi‑agent, observable pipelines.\n\nRelevance: By mid‑2026 enterprises prioritize governance, observability, lifecycle management and data residency while integrating large models from providers such as Anthropic Claude, AWS Bedrock and OpenAI. The shift to multi‑agent orchestration addresses complex use cases (multi‑step approvals, automated procurement, developer productivity) and surfaces needs for cost control, auditability and role‑based access.\n\nKey tools and roles: Kore.ai targets enterprise-grade, governed multi‑agent workflows with no‑code to pro‑code tooling and observability features. LangChain is a developer‑first agent framework and commercial platform providing SDKs for building, testing and deploying LLM‑powered agents. AgentGPT offers an accessible browser‑based, no‑code way to prototype autonomous agents from templates. GPTConsole is focused on developer workflows — SDK, API, CLI and event‑chaining for production agents with memory and lifecycle controls. Anakin.ai provides a large library of ready apps for business automation in low‑code environments, and Tabby offers a self‑hosted, local‑first coding assistant for secure model serving and IDE integration.\n\nTaken together, these platforms reflect a maturing market where enterprises choose combinations of managed models, agent frameworks and low‑code orchestration to meet compliance, integration and scalability requirements without sacrificing developer control.