Multi-agent orchestration is the coordination of several specialized AI agents to complete a process that no single agent owns end to end. An orchestrator routes work between agents, manages shared context and handoffs, and sequences their actions across systems so the overall workflow reaches a reliable outcome.
Also known as: multi-agent workflow
Real enterprise processes span departments and systems — intake, validation, decisioning, fulfillment. Orchestration lets a purpose-built agent handle each step while a coordinating layer manages handoffs, state, and exceptions.
watsonx Orchestrate provides the orchestration layer for collaborating agents and tools. Incede.ai designs the agents, their boundaries, and the handoffs so multi-agent workflows stay governed and observable.
AI systems that take action — applying logic, making decisions, and running multi-step workflows end to end across enterprise systems, with human oversight.
Read definition →Agentic AIA software component that pursues a goal by perceiving context, reasoning about what to do, and acting through tools and APIs — then iterating on the result.
Read definition →ArchitectureThe operating layer to deploy, monitor, secure, and govern an entire fleet of AI agents from one place — managing the agentic estate at scale.
Read definition →ArchitectureAn open protocol that lets AI agents from different frameworks or vendors discover one another and collaborate through a common interface.
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