CrewAI logo

CrewAI

Free tier

The open platform that accelerates enterprise agent adoption at scale

Free tier available·All audiences·Powered by Multi-LLM (model-agnostic)·API available·Open source

Key strengths

Used by 63% of the Fortune 500Supports no-code visual editor and code-first Python APIRole-based multi-agent orchestration with deterministic workflowsFull observability with real-time LLM/tool call tracing and cost accountingContinuous agent improvement via automated training and multi-LLM testing
Free tier + paid plans
United States
Founded 2023
Self-hostable
No ratings yet

Developer Documentation

CrewAI provides a robust developer experience with multiple integration surfaces:

Installation

pip install crewai

Core Concepts

  • Agents — Role-based entities with defined goals, backstories, and tool access.
  • Tasks — Discrete units of work assigned to agents.
  • Crews — Orchestrated groups of agents collaborating on a shared objective.
  • Flows — Deterministic, controllable pipelines for complex multi-agent orchestration.

Code-First Example

from crewai import Agent, Task, Crew

researcher = Agent(role='Researcher', goal='Find key insights', ...)
writer = Agent(role='Writer', goal='Summarize findings', ...)
task = Task(description='Research and summarize AI trends', agent=researcher)
crew = Crew(agents=[researcher, writer], tasks=[task])
result = crew.kickoff()

Enterprise Features (Control Plane)

  • Real-time tracing of every LLM call, tool call, and memory read
  • RBAC with immutable audit trails and Enterprise IAM integration
  • Human-in-the-loop intervention gates during execution
  • Runtime hooks for PII redaction and policy enforcement at every LLM/tool boundary
  • Multi-LLM model swapping at runtime for cost/performance optimization

Full API reference and CLI docs are available at docs.crewai.com.