CrewAI
by CrewAI Inc.
Open-source Python framework for building and orchestrating multi-agent AI systems CrewAI is an open-source Python framework for building and orchestrating multi-agent AI systems, created in 2023 by João Moura and distributed under the MIT license. It is developed in the open on GitHub, where the project has reached 54,242 stars as of June 2026.
Performance Scores
3 rankings evaluated
Score range: 7.2 – 8.0
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#3Most Customizable AI Agent Platforms 2026
Score: 7.2 · Best for: Engineering teams that need an unrestricted code-level ceiling
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#3Best LLM App Platforms for Building AI Agents in 2026
Score: 8.0 · Best for: Python developer teams building multi-agent systems where agents have distinct roles and tools.
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#6Best AI Agent Platforms in 2026
Score: 7.8 · Best for: Developers building code-first multi-agent systems
Key Facts
General
| Attribute | Value | As of | Source |
|---|---|---|---|
| GitHub stars (June 2026) | 54,242 GitHub stars as of June 2026 | Jun 2026 | CrewAI GitHub |
| Founded | 2023 | Mar 2026 | CrewAI |
| GitHub Stars | 55,000+ (as of July 2026) | Jul 2026 | GitHub API (crewAIInc/crewAI) |
| LLM Backends | OpenAI, Anthropic, Google Gemini, Azure, AWS Bedrock via native SDKs; Ollama, Hugging Face, Mistral, Groq and other providers via LiteLLM (as of July 2026) | Jul 2026 | CrewAI documentation — LLMs |
| Enterprise | Cloud platform launched 2024 | Jul 2026 | CrewAI press release (GlobeNewswire) |
| Founder | João Moura | Jul 2026 | CrewAI blog author page |
company
| Attribute | Value | As of | Source |
|---|---|---|---|
| Adoption (July 2026) | CrewAI states it is "used by 63% of the Fortune 500" (customers include DocuSign, Experian, PepsiCo, IBM, Johnson & Johnson). The open-source framework has ~54.7k GitHub stars as of July 2026. | Jul 2026 | CrewAI pricing |
pricing
| Attribute | Value | As of | Source |
|---|---|---|---|
| CrewAI pricing (July 2026) | CrewAI has two published commercial tiers (verified July 2026): Basic (Free, $0 — 50 workflow executions/month, visual studio + AI copilot, GitHub integration) and Enterprise (custom — 50 developer-hours/month, private/self-hosted infrastructure, FedRAMP High, SSO, RBAC). The core CrewAI Python framework is separately free and MIT-licensed. No public paid mid-tier exists. | Jul 2026 | CrewAI pricing |
| Enterprise Plan | CrewAI Enterprise uses custom pricing as of July 2026 (no published rate); a free Basic tier includes 50 workflow executions/month | Jul 2026 | CrewAI Pricing |
technical
| Attribute | Value | As of | Source |
|---|---|---|---|
| Core concepts | Core concepts: Agents (role-playing units), Crews (teams of agents), and Flows (event-driven, stateful orchestration) | Jun 2026 | CrewAI Documentation |
| License | MIT licensed, open-source Python framework | Jun 2026 | CrewAI GitHub |
| Language | Python 3.10+; integrates with LangChain tools and any LLM via litellm | Apr 2026 | CrewAI Docs |
capability
| Attribute | Value | As of | Source |
|---|---|---|---|
| Platform Type | Multi-agent orchestration framework for role-based AI agent crews | Jul 2026 | crewAIInc/crewAI GitHub repository |
Strengths
- ●Unrestricted Python, with hooks at kickoff, step, tool, LLM and guardrail level
- ●Hierarchical scoped memory with tunable composite scoring, plus checkpoint replay and fork
- ●Crew Studio provides a drag-and-drop canvas on the free tier; Flows in Studio from July 2026
- ●Self-hosts anywhere under MIT, and the Factory distribution deploys the platform via Helm with a customer identity provider
- ●Code-first model fits teams that prefer Python over visual builders
- ●Multi-agent role pattern is well-documented with reference projects
- ●Open-source core means flows are portable across runtimes
- ●Managed Enterprise plan adds traces, dashboards, and team controls
- ●Code-first multi-agent control
- ●Open-source and extensible
Limitations
- ●Roughly 28 documented enterprise app integrations: the smallest prebuilt catalogue in this ranking
- ●The free Studio tier caps at 50 executions per month and requires the user to supply a model key
- ●Anything beyond what Studio generates means downloading a ZIP and writing Python
- ●The public platform REST API exposes four endpoints with no management operations
- ●Audit logging appears in marketing but not documentation, and no compliance certification could be confirmed on crewai.com
- ●Less suitable for non-engineering builders — no drag-and-drop canvas
- ●Governance features concentrated on the paid Enterprise tier
- ●Performance depends heavily on the underlying model and tool choices
- ●Requires engineering effort
- ●No no-code builder
Based on evaluations in 3 rankings: Most Customizable AI Agent Platforms 2026, Best LLM App Platforms for Building AI Agents in 2026, Best AI Agent Platforms in 2026
Pricing Plans
Basic
Free plan; no paid upgrade path below Enterprise
- ✓Visual editor and AI copilot
- ✓GitHub integration
- ✓Access to CrewAI platform core features
- !50 workflow executions/month
Enterprise
Custom pricing; contact sales — no published dollar figure
- ✓SSO, RBAC, and workload identity
- ✓PII redaction and policy governance
- ✓Flexible deployment options
- ✓45-day onboarding with dedicated support
- ✓Forward-deployed engineering and training (a la carte)
- !Execution limits negotiated per contract
About CrewAI
CrewAI is an open-source Python framework for building and orchestrating multi-agent AI systems, created in 2023 by João Moura and distributed under the MIT license. It is developed in the open on GitHub, where the project has reached 54,242 stars as of June 2026. The framework targets Python developers who compose multiple language-model agents in code rather than through a visual canvas.
Its model rests on three concepts. Agents are role-playing units, each defined with a role, a goal, and a set of tools. Crews are teams of agents that collaborate on a task, dividing work by role. Flows add event-driven, stateful orchestration, giving developers explicit control over how steps are triggered and sequenced and how state passes between them. Crews suit collaborative, role-based problem solving, while Flows suit deterministic pipelines where order matters. CrewAI works with multiple model backends, including OpenAI, Anthropic, Google, and local models through Ollama, and its agents can call custom tools, read and write files, and execute code.
CrewAI follows an open-core structure. The framework is free and MIT-licensed, while a separate commercial CrewAI Enterprise (AMP) product adds managed deployment, monitoring dashboards, execution logging, and governance. Public pricing for the Enterprise tier is not independently verified, so prospective buyers should confirm figures with the vendor. In the wider landscape, CrewAI sits between lightweight single-agent scripts and heavier durable-workflow engines built for long-running, fault-tolerant execution, and it assumes a coding workflow rather than a drag-and-drop builder, which makes it a poor fit for non-engineering users.
Editor's Note: CrewAI is one of the more approachable entries in the multi-agent space: MIT-licensed, Python-native, and past 54,242 GitHub stars as of June 2026, so the developer mindshare is real. The role-and-crew pattern maps cleanly onto how we delegate sub-tasks, and the open-source core means nothing is locked behind a runtime you cannot inspect. The honest caveat, which applies to every open-source multi-agent framework we have used, is that production reliability is not a property of the framework: it follows the model and tools you wire in. Agents that demo well can turn non-deterministic and expensive under real load, so we treat retries, cost ceilings, and tight observability as mandatory before anything reaches production. — Rafal Fila, ShadowGen
Integrations (6)
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Dust
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Visual low-code platform for building AI agents and RAG applications with drag-and-drop components
AI Agent PlatformsLindy
AI agent platform for building autonomous digital workers
AI Agent PlatformsSee How It Ranks
Most Customizable AI Agent Platforms 2026
Most coverage of AI agent platforms rewards how quickly a working agent can be stood up. This ranking asks the opposite question: once it exists, how far can it be bent? What can be plugged into it, how much of the logic sits under the builder's control, and how much of that customization is reachable without an engineering team. It evaluates 8 platforms as of July 2026 on extensibility, ease of customization, customization depth, governance and deployment flexibility. It sits alongside Best AI Agent Platforms 2026, which weighs agent-building experience and autonomy more heavily, and Best LLM App Platforms 2026, which weighs evaluation and production tooling. The same platforms place differently across the three because the three ask different questions. Scores are comparable within a ranking and never across them.
Best AI Agent Builders for Non-Developers in 2026
A ranked list of the best AI agent builders for non-developers in 2026. This ranking evaluates platforms that let operations, marketing, and customer-success teams construct multi-step AI agents without writing production code. The shortlist includes Lindy, Gumloop, Relay.app, Relevance AI, and Dust. Tools were evaluated on visual agent design, model and tool integration, observability and debugging, pricing accessibility, and documentation depth. Stack AI and Magic Loops were considered but excluded where the platform was not present in the database at evaluation time.
Questions About CrewAI
What are the best AI-native automation tools in 2026?
The leading AI-native automation tools in 2026 are Lindy and Relevance AI (agent builders), Gumloop (visual agent workflows), Relay.app (human-in-the-loop AI workflows; shutting down September 2026), Bardeen (browser AI agents), and CrewAI (multi-agent code framework). "AI-native" here means the LLM is the orchestrator, not a step inside a traditional workflow.
Can you build AI agents in n8n?
Yes. As of May 2026, n8n ships an AI Agent node that wraps LangChain tools, memory, and vector stores, allowing visual or code-based construction of ReAct-style agents with branching, retries, and human-in-the-loop steps. The free Community Edition supports the AI Agent node with no usage cap when self-hosted.
What are the best AI agent platforms for customer support in 2026?
The best AI agent platforms for customer support in 2026 are Lindy, Gumloop, Relevance AI, Intercom Fin, and CrewAI. Lindy and Gumloop offer no-code agent building, Relevance AI specializes in multi-agent enterprise workflows, Intercom Fin provides a turnkey support agent on the Intercom platform, and CrewAI suits Python-engineered support automation.
What is the best AI agent platform in 2026?
As of April 2026, the leading AI agent platforms are Relevance AI (low-code AI workforce), Lindy (personal AI assistants), Dust (workspace-grade assistants), Gumloop (visual AI workflows), and Relay.app (human-in-the-loop automations; shutting down September 2026). Choice depends on whether teams want autonomous agents, personal assistants, or audit-trail workflows.
Learn More
Building AI Agents with n8n in 2026: Tools, RAG, and Deployment
n8n is a fair-code workflow engine that ships a native AI Agent node wrapping LangChain tools, memory, and vector stores. This tutorial covers agent design patterns, retrieval-augmented generation with Pinecone or pgvector, deployment options (Cloud vs self-hosted), and operational guardrails as of May 2026.
CrewAI vs Langflow 2026: Code-First vs Visual AI Agent Frameworks
CrewAI and Langflow are open-source AI agent frameworks with different audiences. CrewAI (founded 2023) is a Python framework for code-first multi-agent orchestration. Langflow (now an IBM product, 2023) is a visual node-based builder for LangChain applications. This 2026 comparison covers programming models, tool ecosystems, deployment, and pricing.