> For the complete documentation index, see [llms.txt](https://docs.workfx.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.workfx.ai/workfx-companion-agent-knowledge/workforce-factory/multi-agent.md). # Multi-Agent **Multi-Agent** systems in Workforce Factory enable you to orchestrate multiple specialized agents to collaboratively solve complex tasks through intelligent coordination and delegation. Unlike single agents that handle tasks independently, multi-agent systems leverage the combined expertise of multiple agents to achieve outcomes that exceed individual agent capabilities. ## Overview Multi-Agent systems in Workforce Factory provide two primary orchestration patterns: * **Supervisor-Managed**: A supervisor agent autonomously coordinates and delegates tasks to specialized worker agents based on their expertise * **Manual Orchestration**: Individual agents function as nodes in a workflow, giving you direct control over task routing and data flow ## Key Components ### Supervisor Architecture The supervisor acts as an intelligent coordinator that: * Analyzes incoming requests and breaks them into sub-tasks * Selects appropriate worker agents based on their specializations * Delegates tasks autonomously without manual intervention * Aggregates results from multiple agents into cohesive responses ### Agent Nodes Published agents can be imported as individual nodes, allowing you to: * Maintain manual control over task execution flow * Configure specific input parameters for each agent * Build complex workflows that combine multiple specialized agents * Create deterministic processes with predictable outcomes ## When to Use Multi-Agent Multi-agent systems are ideal for: * **Complex Problem Solving**: Tasks requiring multiple areas of expertise (research + analysis + reporting) * **Parallel Processing**: Independent sub-tasks that can be executed simultaneously by different agents * **Specialized Workflows**: Processes where different agents excel at specific types of work * **Scalable Operations**: Systems that need to adapt based on workload complexity --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://docs.workfx.ai/workfx-companion-agent-knowledge/workforce-factory/multi-agent.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.