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CrewAI
Framework for defining roles, tasks, and crews of agents that hand work to each other. Aimed at developers building multi-agent systems.
Builders experimenting with role-based agent crews who will measure whether extra agents improve the task.
Teams that need a proven single-agent production path and do not want to debug agent-to-agent chatter.
Founded by João Moura.
Verdict
CrewAI is a good fit for builders who want a multi-agent workflow where distinct roles collaborate on a shared task. The open framework keeps early cost low; paid tiers show up when you want hosted control and support. It makes the crew pattern easy to demo, and clients like the mental model. Just know most production wins still come from one well-scoped agent plus tools.
Score Breakdown
How CrewAI scores in the categories that matter to its buyers.
Pricing
CrewAI publishes a free hosted Basic tier for its agent management platform, with Enterprise sold by quote. The open-source Python framework remains free under MIT. Prices below are USD from CrewAI’s public rate card as of September 2026.
| Plan | Executions / month | Price | What stands out |
|---|---|---|---|
| Basic | 50 | $0 | Visual editor, AI copilot, GitHub integration, tracing |
| Enterprise | Custom | Sales quote | SSO, RBAC, VPC or self-host deploy, 45-day onboarding |
The Field at a Glance
How CrewAI compares with other multi-agent / swarm tooling and nearby agents & orchestration vendors we reviewed, by Overall Score and relative typical engagement cost.
CrewAI scores 6.9 on this chart of multi-agent / swarm tooling and nearby agents & orchestration vendors, under LlamaIndex (8.1), Agno (8.0), LangChain (8.0), Dify (7.5), n8n (7.5), and deepset (7.1), and ahead of Zapier (6.7) and Sema4.ai (6.3). Relative cost lands upper for this set.
Use-case matrix
| Use case | Fit | Notes |
|---|---|---|
| Role-based agent prototypes | Strong | Clear mental model for a first crew. |
| Research or drafting swarms | Mixed | Works when you cap steps and cost. |
| Customer-facing agent fleets | Poor | Needs more control than the framework supplies. |
| Replacing a workflow engine | Poor | Crews are not a substitute for orchestration with SLAs. |
Who it’s for
Good fit
- Labs testing whether multiple roles beat one agent
- Internal tools with a human checking the output
- Teams that can write evals before they scale the crew
Poor fit
- Buyers shopping for a managed swarm product
- Latency-sensitive support flows
- Projects without an eval harness
Review Excerpts
Below are excerpts from public reviews. Paid reviews and pay-for-play sites such as Clutch were excluded.
“After spending a lot of time on it for my own projects, I became very disappointed with AutoGen and CrewAI.”
“whereas autogen and crewAI are complete lost cases unless using only the strongest most expensive models.”
“i've been using loads of ai agent frameworks (crewai, langgraph, autogen) and i just don't get why they are so popular.”
“On the other hand, in all of the use-cases I tried I ended up spending hours analysing the logs and results trying to make it work repeatedly. It is also incredibly slow (in my case one run takes 5–10 minutes), which is mostly due to the planning and thinking process.”
“In the end, by the time I had the crew working I would have had the use-case implemented like 10 times if I used LLM API directly.”
“CrewAI can be resource-heavy. Running multiple agents simultaneously ate through my API credits faster than I expected. That Dubai project cost about $180 in API fees during the first month of testing.”
Company Facts
- Founded
- 2024 (CB Insights)
- Headquarters
- Middletown, Delaware, United States (CB Insights)
- Total funding raised
- $18M (CB Insights)
- Key investors
- Craft Ventures, Earl Grey Capital, Andrew Ng, Alt Capital, Insight Partners (CB Insights)
- Customers
- Konecta and Docusign (CB Insights)
- Website
- crewai.com
Key Leadership
João Moura
Founder and CEO
Methodology
This page is an independent evaluation of CrewAI for buyers comparing options in multi-agent & swarm tooling. AI Industry Reviews accepts no sponsorships, advertising, or pay-for-placement fees. CrewAI did not pay for this review.
What we scored
The headline number is an Overall Score on a 0-10 scale. Eight criteria fall under it in two groups.
- Buyer outcomes (for multi-agent & swarm tooling)
- Role &
- crew design
- Handoff clarity
- Production control
- Eval fit
- Company & commercial
- Innovation &
- product leadership
- Project management &
- communication
- Pricing
- Contract fairness
Pricing measures whether the price looks fair for the value delivered, including packaging and renewal friction that show up in real buying cycles.
Score Composition
| Input | Weight | What it covers |
|---|---|---|
| Reviews | 40% | A proprietary read of what practitioners say about likes, complaints, and day-to-day use, including public review sites, forums, and private chat rooms. Paid reviews and pay-for-play sites such as Clutch are out of scope. |
| Product | 35% | Hands-on look at screens and workflows. |
| Pricing | 15% | Whether the price looks fair for what you get. |
| Docs & training | 10% | Docs, tutorials, and training material. |
How we balanced the evidence
The Overall Score is the simple average of the eight criteria. Recommendation language follows that score and the fit pattern described above.
Scope
CrewAI is graded here as multi-agent & swarm tooling. Criteria scores can move as more review volume and product checks are added.