A multi-agent orchestration framework that organizes autonomous agents into teams with defined roles and collaboration patterns.
CrewAI is an open-source multi-agent orchestration framework that models complex tasks as collaborative work by a "crew" of specialized autonomous agents, each with a defined role, goal, backstory, and set of available tools.
The key insight behind CrewAI is that many complex knowledge work tasks benefit from role specialization and collaboration—just as human teams combine specialists (researcher, analyst, writer, critic) to produce better outcomes than any single generalist.
Core CrewAI concepts:
Agents are the individual actors in a crew. Each agent has a role (e.g., "Senior Research Analyst"), a goal (e.g., "Produce accurate, cited research summaries"), a backstory (personality context for the LLM), and a set of tools it can use.
Tasks are the specific work items assigned to agents, with clear descriptions, expected outputs, and optional assignment to specific agents.
Crews coordinate groups of agents to complete a set of tasks. CrewAI supports both sequential task execution (output of one task feeds the next) and hierarchical task management (a manager agent delegates to worker agents).
Flows (introduced in CrewAI v0.60+) provide event-driven workflow orchestration, allowing crews to be integrated into larger application architectures.
CrewAI excels at knowledge-intensive tasks: market research reports, content creation pipelines, code review workflows, and competitive intelligence gathering. Its role-based model produces noticeably more structured, comprehensive outputs compared to single-agent approaches on these task types.