CrewAI is a code-first framework for building “crews” of AI agents that collaborate on tasks using tools, processes, and optional tracing for debugging and visibility into agent runs.
CrewAI is a framework for building multi-agent systems, where multiple agents collaborate as a crew to complete work.
You define agents, assign them tasks, and run them as a crew (commonly via a kickoff() style run), using structured concepts instead of a single “chat prompt.”
CrewAI also documents tracing capabilities for monitoring and debugging agent runs during development and production use.
CrewAI is best suited for developers and AI builders who want to implement multi-agent workflows in code, with explicit control over agent roles, tasks, tools, and execution logic.
Agents and tasks are defined in Python and executed together as a crew.
A "crew" is the orchestration unit that groups agents and tasks and executes them together.
Agents can be configured with tools and memory according to CrewAI's documented core concepts.
The CrewAI framework is open-source and free to use under the MIT license. Commercial or enterprise offerings may be available; details are provided directly by CrewAI.
CrewAI is centered on “crews” (multi-agent orchestration as a primary abstraction), while LangChain is a broader code framework for LLM apps/agents; both are code-first approaches.
Learn more about LangChainCrewAI is code-first, while Dify is positioned as an LLM app platform with a UI; both can be used for agent workflows, but they target different build styles (code vs platform UI).
Learn more about DifyLast updated: December 2025
Multi-Agent Framework