CrewAI vs DeepAgents
Side-by-side comparison of features, pricing, and ratings
At a glance
| Dimension | CrewAI | DeepAgents |
|---|---|---|
| Pricing | Contact for pricing (enterprise) | Free (open source) |
| Target Audience | Enterprise teams needing governance | Developers building production agents |
| Core Strength | Multi-agent orchestration with discovery, governance, and observability | Batteries-included agent harness with sub-agents, filesystem, human-in-the-loop |
| Open Source | Core library open source, platform is enterprise | Yes |
| Model Agnostic | Yes, with multi-LLM testing | Yes (any LLM with tool calling) |
| Governance | RBAC, immutable audit trails, PII redaction hooks, approval gates | Human-in-the-loop approval, basic audit trails via LangSmith |
Choose DeepAgents if you need a free, fully open-source agent harness with sub-agents, filesystem access, and human oversight for complex multi-step tasks. Choose CrewAI if you're an enterprise team that needs governance, discovery of automation opportunities, and observability at scale. DeepAgents is better for agile development; CrewAI for compliance-heavy deployments.
Feature-by-feature
DeepAgents is a production-ready open-source agent harness built on LangGraph. It excels at complex multi-step tasks with features like sub-agents (isolated context windows), pluggable filesystem backends (local, sandboxed, remote), automatic context summarization, sandboxed shell execution, persistent memory, and human-in-the-loop approval for tool calls. It supports any LLM with tool calling (OpenAI, Anthropic, Google, Ollama, vLLM, etc.) and integrates with MCP servers and LangSmith for tracing. The newest capability is Deep Agents Code, a pre-built CLI coding agent.
CrewAI is an enterprise platform for orchestrating multi-agent workflows. It stands out with CrewAI Discovery, which analyzes tickets and chats to rank automation opportunities. It offers a no-code visual editor that exports to Python, alongside a code-first API. Key features include role-based agents, deterministic workflow creation, real-time tracing with cost accounting, RBAC, immutable audit trails, human-in-the-loop approval gates, and runtime hooks for PII redaction. It integrates with tools like Arize, DataDog, and NVIDIA NemoClaw (as per latest news). CrewAI also emphasizes multi-LLM testing and continuous training.
DeepAgents focuses on giving developers a full-featured agent out of the box with sub-delegation and filesystem access. CrewAI focuses on enterprise governance and discovery—helping organizations know what to automate. While DeepAgents is purely open-source, CrewAI offers an open-core model with enterprise features requiring a paid license.
Pricing compared
DeepAgents is entirely free and open source (MIT license). There are no usage limits, pricing tiers, or charges for the agent harness itself. Users only pay for underlying LLM API costs (e.g., OpenAI, Anthropic) if they use paid models. Optional LangSmith usage for tracing and evaluation has its own pricing, but the core framework is free.
CrewAI operates on a contact-for-pricing enterprise model. While the open-source library is free, the platform features (Discovery, governance, observability, RBAC, audit trails) require a paid license. There is no transparent self-serve pricing; interested users must contact sales. According to CrewAI's marketing, it's used by 63% of the Fortune 500, indicating a premium enterprise positioning.
For budget-conscious developers or teams, DeepAgents is the clear winner with zero licensing cost. For enterprises needing compliance, discovery, and support, CrewAI's pricing is justifiable but opaque. DeepAgents offers better value for small teams and individual devs; CrewAI is for organizations with larger budgets and strict governance needs.
Who should pick which
- Solo developer building a coding assistantPick: DeepAgents
DeepAgents is free, open-source, and includes a pre-built CLI coding agent (Deep Agents Code). It supports local models via Ollama and has human-in-the-loop approval, perfect for a solo dev.
- Enterprise compliance officer needing audit trailsPick: CrewAI
CrewAI offers RBAC, immutable audit trails, PII redaction hooks, and approval gates – essential for regulated industries.
- Team lead evaluating automation opportunitiesPick: CrewAI
CrewAI Discovery analyzes existing tickets and chats to rank automation ROI, helping prioritize what to build.
- AI researcher prototyping multi-step agentsPick: DeepAgents
DeepAgents is model-agnostic, supports sub-agents with isolated contexts, and has built-in context management – ideal for rapid prototyping without cost.
- CTO of a mid-size company requiring multi-agent orchestrationPick: CrewAI
CrewAI's role-based agents, deterministic workflows, and real-time tracing with cost accounting provide the control and observability needed for production at scale.
Frequently Asked Questions
Which tool is completely free?
DeepAgents is fully free and open-source. CrewAI has an open-source core but enterprise features require a paid license.
Can I run DeepAgents with local LLMs?
Yes, DeepAgents supports Ollama, vLLM, llama.cpp, and other local model providers.
Does CrewAI support human-in-the-loop?
Yes, CrewAI offers human-in-the-loop approval gates and intervention, along with runtime hooks for policy checks.
Which tool is better for coding agents?
DeepAgents includes a built-in CLI coding agent (Deep Agents Code) and supports shell execution, making it more suited for coding tasks out-of-the-box.
Does CrewAI provide cost tracking?
Yes, CrewAI has full cost accounting for every LLM and tool call, plus real-time tracing.
Can I use CrewAI without contacting sales?
The open-source library is free, but the platform features (Discovery, governance) require contacting sales for pricing.
Which tool is more suitable for enterprise governance?
CrewAI, with RBAC, immutable audit trails, PII redaction, and compliance hooks.
Do both tools support multi-agent architectures?
Yes, DeepAgents uses sub-agents with isolated contexts, while CrewAI uses role-based agents for multi-agent orchestration.
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