LLM orchestration refers to the tooling and patterns used to coordinate large language models with tools, data sources, workflows, and guardrails so they can reliably power complex applications. It matters because production AI systems typically require chaining multiple model calls, integrating with external systems, enforcing safety and compliance, and handling errors and retries—capabilities that raw LLM APIs do not provide on their own.