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Stay free if you only need visual editor + ai copilot and 50 workflow executions/month. Upgrade if you need everything in basic and enterprise connectors and pre-built integrations. Most solo builders can start free.
Why it matters: Pricing is Custom-only — no self-serve mid-tier for teams too big for Free, too small for Enterprise
Available from: Enterprise
Why it matters: Requires a sales conversation before you can evaluate real cost
Available from: Enterprise
Why it matters: Discovery engine's automation ranking depends on quality of your ticket/chat integration
Available from: Enterprise
Why it matters: Enterprise setup (VPC/BYOC) adds cloud-engineering effort vs a SaaS-only competitor
Available from: Enterprise
Why it matters: Advanced feature not available in free plan.
Available from: Enterprise
Why it matters: Store more data and handle larger projects. Prevents hitting usage walls.
Available from: Enterprise
No, you can build entirely in the visual builder without ever touching the SDK. However, many engineering teams prototype in the open-source CrewAI framework (which has 30,000+ GitHub stars and an active community) and migrate the same workflow definitions into Enterprise for production deployment. The bidirectional compatibility means workflows authored in either environment can be imported into the other without rewrites, so teams can mix code-first and visual approaches based on which agents benefit from each.
Yes, CrewAI Enterprise supports every model that the open-source framework supports, including Anthropic Claude, Google Gemini, AWS Bedrock, Azure OpenAI, and locally hosted open-weights models like Llama and Mistral. This is critical for enterprise customers who often have existing model contracts, data residency requirements, or preferences for specific model families. Model routing can be configured per-agent, so a single workflow can use GPT-4 for reasoning steps and a cheaper local model for extraction.
CrewAI Enterprise uses custom pricing based on deployment scale, included executions, and feature requirements rather than a published per-seat tier. Public reporting suggests enterprise contracts can reach approximately $120,000/year, with unlimited seats and up to 30,000 executions included in the base plan. Unlike per-user enterprise AI platforms, this model favors organizations rolling out agent access broadly across departments. Contact CrewAI's sales team directly for a tailored quote based on your requirements.
Yes — CrewAI Enterprise supports both cloud-hosted (managed by CrewAI on their infrastructure) and self-hosted VPC deployments running on your own Kubernetes clusters. Self-hosting is the standard configuration for regulated industries and government customers who require full data sovereignty or air-gapped environments. The tradeoff is that self-hosted deployments require Kubernetes operational expertise on your team and longer initial setup, typically 3-6 months for full production readiness.
Based on our analysis of agent platforms in the directory, CrewAI Enterprise differentiates on the operational and compliance layer rather than the underlying orchestration model. LangGraph and AutoGen are powerful frameworks but ship as libraries — teams must build their own deployment, monitoring, governance, and compliance tooling on top. CrewAI Enterprise bundles managed Kubernetes deployment, real-time cost and execution monitoring, RBAC, audit logging, PII masking, and SOC2 certification into a single vendor-supported platform, which is the value proposition for regulated enterprises.
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Last verified March 2026