Agentic AI

Agent Orchestration

Agent orchestration is the architecture pattern that defines how multiple AI agents are coordinated, prioritized, and managed. An orchestrator agent distributes tasks, monitors progress, resolves conflicts, and ensures all sub-agents work toward a common goal.

Why does this matter?

When companies deploy multiple AI agents, orchestration becomes a success factor. Without it, agents work in isolation or contradictory ways. With good orchestration, individual agents become a powerful system — comparable to a department head coordinating their team.

How IJONIS uses this

We use LangGraph as the orchestration framework with hierarchical and parallel execution graphs. Every orchestrator receives defined routing rules, timeout handling, and fallback strategies. For complex scenarios, we use CrewAI with role-based agents and automatic task distribution.

Frequently Asked Questions

What is the difference between agent orchestration and an agentic workflow?
An agentic workflow describes the overall process — the sequence of steps. Orchestration describes how the participating agents are coordinated within this process: who handles which task, in what order, and what happens on failure.
How many agents do I need before orchestration becomes necessary?
Orchestration is worthwhile starting with two agents that have dependencies. With three to four agents at the latest, it becomes essential to properly handle conflicts, data flows, and error states. Without orchestration, complexity grows exponentially.

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