CrewAI
Build, govern, and optimize multi-agent workflows for business and engineering teams.
Linked from crewai.com · checked 29 Oct
- Tool type
- AI agent builder and runtime
- Made for
- Business, engineering and platform teams
- Runs on
- Hosted cloud; private enterprise deployment
- Basic runs in CrewAI cloud. VPC or customer infrastructure requires an applicable Enterprise agreement.
What it does
CrewAI takes in business processes, tickets, chats, app data, and workflow definitions, and uses them to suggest agent automations ranked by effort, value, and readiness. It produces buildable multi-agent workflows that can be created with a visual canvas editor, exported to Python, or coded directly through an API. Deployed agents run on CrewAI cloud, a customer VPC, or customer infrastructure.
Teams use CrewAI's visual builder for business-side automation and its code-first API for engineering control, with role-based agents separating orchestration. A control plane traces LLM calls, tool calls, and memory reads, supports RBAC, audit trails, and human-in-the-loop approval gates, and injects PII redaction and policy checks. Production runs can be tested across multiple LLMs and evaluated with partner tools such as Arize, Galileo, DataDog, and Patronus.
CrewAI suits organizations building and operating coordinated AI agents with shared controls for business and technical teams. The hosted Basic plan includes a limited monthly execution allowance, while Enterprise agreements can add private deployment and governance features. Teams should map agent responsibilities, test the tools each agent can call and review traces before introducing production data. Model-provider access and infrastructure requirements depend on the deployment, and Enterprise capacity and overage terms should be agreed during onboarding.
What it can do
- Agentic use case discovery that ranks automation opportunities by effort, value, and readiness.
- Visual no-code workflow editor exportable to Python, plus a code-first API.
- Role-based agent orchestration and deterministic workflow creation.
- Real-time tracing of LLM calls, tool calls, and memory reads with cost accounting.
- RBAC, immutable audit trails, human-in-the-loop approval gates, and runtime PII redaction and policy checks.
- Multi-LLM testing for model swapping and evaluation integrations with Arize, Galileo, DataDog, and Patronus.
Works with
- Arize
- Galileo
- DataDog
- Patronus
- GitHub
- Slack
- Microsoft Teams
- Gmail
- Salesforce
- Amazon Bedrock Agents
Example workflows
- Discover and build an automation
- Illustrative example. Input: connected tickets, chats, and workflow data. Steps: run Discovery to get ranked automation opportunities, pick one, and generate it with the automated multi-agent builder. Output: an editable multi-agent workflow that can be exported to Python.
- Govern and review a running agent
- Illustrative example. Input: a deployed multi-agent workflow with approval requirements. Steps: enable tracing and RBAC, set PII redaction and policy checks, and route sensitive actions to a human approver through the approval gate. Output: an auditable run history with traced LLM and tool calls and human sign-off records.
Before you choose
- Basic has a hard maximum of 50 workflow executions per month.
- Private deployments, enterprise governance and overage require an applicable agreement.
- Test agent actions and account for external model and infrastructure requirements.
Listed under
Get started
Free plan available; Enterprise requires a trial request or sales contact.
- Create an account at the sign-up page and choose the Basic plan.
- Build a first agentic workflow with the visual editor or by installing the CrewAI package and following the quickstart.
- Connect integrations such as GitHub, Slack or Teams, and configure RBAC and tracing for team use.
Plans and prices
Prices in USDBasic is free with a maximum of 50 workflow executions per month and no overage. Enterprise uses custom pricing and can include flexible overage, private deployment and governance. Confirm capacity, model-provider costs and trial terms in the agreement.
- Visual editor and AI copilot
- 50 workflow executions/month
- SSO, RBAC, workload identity, PII redaction, and policies
- 45-day onboarding
Source: crewai.com/pricing, checked 29 Oct 2026. Prices can change; check before you buy.
Sources for this overview
Product pages, documentation, and pricing checked 29 Oct 2026. Each source supports part of the overview; availability and prices can change.
- CrewAI ↗crewai.com
- Pricing | CrewAI ↗crewai.com
- CrewAI Documentation - CrewAI ↗docs.crewai.com
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Last checked 29 Oct 2026. Every field keeps its source and date; unknown means we couldn’t confirm it.