Multi-AI agent orchestration covers the tools and frameworks used to compose, run, monitor, and govern systems made of multiple specialized AI agents and models. As enterprises push AI past single‑model assistants into coordinated workflows, demand has grown for orchestration layers (agent frameworks), automation platforms that integrate with business systems, and marketplaces for reusable agents. By 2026 this space emphasizes operational concerns: privacy and governance, observability and testing, integrations with enterprise apps, and options for managed vs. self‑hosted deployments. Representative offerings span use cases and technical approaches. Vertex AI provides a unified, fully managed cloud stack for model lifecycle and deployment. MindStudio targets rapid design and deployment with a no‑/low‑code visual interface and enterprise controls. CrewAI and similar frameworks offer developer‑centric, open orchestration primitives (crews/flows) plus visual editors for building multi‑agent pipelines. Synthreo (formerly BotX) focuses on managed enterprise agent fleets and connectors to CRM/ERP systems. Specialized tooling addresses gaps in productionization: Mistral AI supplies efficient foundation models and production tooling with governance focus; RagaAI adds testing, observability, guardrails and debugging for agentic systems; LlamaIndex facilitates document agents and retrieval‑augmented generation; Warp embeds agents into developer workflows as an Agentic Development Environment. Developer‑centric coding agents and quality tools — Qodo (Codium), Cline, Tabnine — and LLM platforms like Cohere provide model, embedding, and retrieval services that agents rely on. Selecting across agent frameworks, automation platforms, and marketplaces now requires balancing control (self‑hosting, governance), velocity (no‑code builders, managed services), and reliability (observability, testing), making orchestration platforms a focal point for enterprise AI adoption.