Sep 2025 → Mar 2026: daily download rate tripled. Second-largest Python agent framework by volume.
CrewAI
active#2 Python agent framework — 5.7M PyPI downloads/month (3× growth in 6 months), Fortune 500 customers (PwC, IBM, Capgemini, NVIDIA, DocuSign), YAML-driven role-based orchestration rated 'fastest to prototype' in 2026 independent reviews. CVE-responsive: gitpython path traversal fixed in v1.11.0.
73/100
Trust
47K+
Stars
4
Evidence
Repo health
13h ago
Last push
401
Open issues
6,284
Forks
284
Contributors
Editorial verdict
Second-largest Python deployment footprint with real Fortune 500 adoption. Consistently rated 'fastest to prototype' — not marketing copy but backed by independent consensus. The right default for role-based business workflow automation teams prioritizing speed. Trade off: observability less mature than LangGraph without AMP Suite.
Source
GitHub: crewAIInc/crewAI
Docs: docs.crewai.com
Public evidence
Not just self-reported — Fortune 500 names confirmed across multiple independent industry publications.
Proactive CVE patching in v1.11.0. Security posture is better than peers at this stage.
'40% faster to production with CrewAI' is a widely-cited independent finding, not marketing copy. YAML-driven config is the mechanism.
How does this compare?
See side-by-side metrics against other skills in the same category.
Where it wins
5.7M PyPI downloads/month — 3× growth in 6 months
Named Fortune 500 customers: PwC, IBM, Capgemini, NVIDIA, DocuSign (multi-source confirmed)
YAML-driven config, role-based crew orchestration — consistently rated 'easiest to prototype with'
89 commits in last 30 days; v1.11.0 released 2026-03-18
Active CVE response — gitpython path traversal fixed in v1.11.0
CrewAI AMP Suite: enterprise tracing, RBAC, unified control plane
Where to be skeptical
Observability less mature than LangGraph without AMP Suite
For complex long-running stateful workflows, LangGraph's architecture is more appropriate
Ranking in categories
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Raw GitHub source
GitHub README peek
Constrained peek so you can sanity-check the source material without leaving the site.
Fast and Flexible Multi-Agent Automation Framework
CrewAI is a lean, lightning-fast Python framework built entirely from scratch—completely independent of LangChain or other agent frameworks. It empowers developers with both high-level simplicity and precise low-level control, ideal for creating autonomous AI agents tailored to any scenario.
- CrewAI Crews: Optimize for autonomy and collaborative intelligence.
- CrewAI Flows: The enterprise and production architecture for building and deploying multi-agent systems. Enable granular, event-driven control, single LLM calls for precise task orchestration and supports Crews natively
With over 100,000 developers certified through our community courses at learn.crewai.com, CrewAI is rapidly becoming the standard for enterprise-ready AI automation.
CrewAI AMP Suite
CrewAI AMP Suite is a comprehensive bundle tailored for organizations that require secure, scalable, and easy-to-manage agent-driven automation.
You can try one part of the suite the Crew Control Plane for free
Crew Control Plane Key Features:
- Tracing & Observability: Monitor and track your AI agents and workflows in real-time, including metrics, logs, and traces.
- Unified Control Plane: A centralized platform for managing, monitoring, and scaling your AI agents and workflows.
- Seamless Integrations: Easily connect with existing enterprise systems, data sources, and cloud infrastructure.
- Advanced Security: Built-in robust security and compliance measures ensuring safe deployment and management.
- Actionable Insights: Real-time analytics and reporting to optimize performance and decision-making.
- 24/7 Support: Dedicated enterprise support to ensure uninterrupted operation and quick resolution of issues.
- On-premise and Cloud Deployment Options: Deploy CrewAI AMP on-premise or in the cloud, depending on your security and compliance requirements.
CrewAI AMP is designed for enterprises seeking a powerful, reliable solution to transform complex business processes into efficient, intelligent automations.
Table of contents
- Why CrewAI?
- Getting Started
- Key Features
- Understanding Flows and Crews
- CrewAI vs LangGraph
- Examples
- Quick Tutorial
- Write Job Descriptions
- Trip Planner
- Stock Analysis
- Using Crews and Flows Together
- Connecting Your Crew to a Model
- How CrewAI Compares
- Frequently Asked Questions (FAQ)
- Contribution
- Telemetry
- License
Why CrewAI?
<div align="center" style="margin-bottom: 30px;"> <img src="https://raw.githubusercontent.com/crewAIInc/crewAI/main/docs/images/asset.png" alt="CrewAI Logo" width="100%"> </div>CrewAI unlocks the true potential of multi-agent automation, delivering the best-in-class combination of speed, flexibility, and control with either Crews of AI Agents or Flows of Events:
- Standalone Framework: Built from scratch, independent of LangChain or any other agent framework.
- High Performance: Optimized for speed and minimal resource usage, enabling faster execution.
- Flexible Low Level Customization: Complete freedom to customize at both high and low levels - from overall workflows and system architecture to granular agent behaviors, internal prompts, and execution logic.
- Ideal for Every Use Case: Proven effective for both simple tasks and highly complex, real-world, enterprise-grade scenarios.
- Robust Community: Backed by a rapidly growing community of over 100,000 certified developers offering comprehensive support and resources.
CrewAI empowers developers and enterprises to confidently build intelligent automations, bridging the gap between simplicity, flexibility, and performance.
Getting Started
Setup and run your first CrewAI agents by following this tutorial.

Learning Resources
Learn CrewAI through our comprehensive courses:
- Multi AI Agent Systems with CrewAI - Master the fundamentals of multi-agent systems
- Practical Multi AI Agents and Advanced Use Cases - Deep dive into advanced implementations
Understanding Flows and Crews
CrewAI offers two powerful, complementary approaches that work seamlessly together to build sophisticated AI applications:
-
Crews: Teams of AI agents with true autonomy and agency, working together to accomplish complex tasks through role-based collaboration. Crews enable:
- Natural, autonomous decision-making between agents
- Dynamic task delegation and collaboration
- Specialized roles with defined goals and expertise
- Flexible problem-solving approaches
-
Flows: Production-ready, event-driven workflows that deliver precise control over complex automations. Flows provide:
- Fine-grained control over execution paths for real-world scenarios