crewAIInc/crewAI

Framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks.

What it solves

CrewAI is a framework for building production-ready multi-agent AI systems. It solves the challenge of orchestrating multiple specialized AI agents to work together autonomously while providing developers with the ability to maintain precise, event-driven control over the overall workflow.

How it works

CrewAI uses two primary abstractions to manage AI agents:

  • Crews: These are teams of role-based agents with defined goals and backstories. They collaborate autonomously to solve complex tasks through dynamic delegation and decision-making.
  • Flows: These are event-driven automations that provide deterministic control. They allow developers to define execution paths, manage state, and use conditional branching (using operators like and_ and or_) to route tasks.

Developers can combine these two—using Flows to orchestrate high-level logic and Crews to handle the autonomous, collaborative intelligence required for specific tasks.

Who it’s for

It is designed for developers and organizations looking to move AI agent prototypes into production-grade automation, specifically those who need a balance between agent autonomy and strict workflow governance.

Highlights

  • Role-Based Collaboration: Agents are defined by roles, goals, and backstories to simulate specialized expertise.
  • Event-Driven Workflows: Flows allow for precise routing and state management between tasks.
  • Python-Native: Offers high-level abstractions and low-level APIs for deep customization of prompts and execution logic.
  • Production-Ready Patterns: Supports structured outputs, human-in-the-loop review, memory, and async execution.
  • Comprehensive Tooling: Includes a CLI for project scaffolding and native support for MCP/A2A.

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