CrewAI vs Dust
A side-by-side comparison of CrewAI and Dust, drawn from Ignaite's continuously-verified listings.
Compared from listings verified as of
Dust
AgentEnterprise platform for building and sharing custom AI agents on company knowledge.
View DustAt a glance
| Attribute | CrewAI | Dust |
|---|---|---|
| Category (differs) | Orchestration | Agent |
| Pricing (differs) | FREEMIUM | PAID |
| License | Open core | Open core |
| Deployment (differs) | — | Hybrid |
| Platforms (differs) | API, CLI | Web, API |
| Model support (differs) | Model-agnostic | Multi-model |
| Vendor (differs) | crewAIInc | Dust |
The honest brief
CrewAI
Models work as a crew of role-typed agents that delegate to each other, built standalone rather than on LangChain.
- Role-based multi-agent model
- Independent of LangChain
- Model-agnostic
- Good for research pipelines
- Opinionated structure
- Less flexible than graph frameworks
- Debugging multi-agent runs is hard
Dust
Org-wide 'multiplayer' AI over shared company knowledge — agents are built once and reused across teams, not siloed per user.
- Agents shareable across the org
- Broad workspace connector library
- Per-agent choice of frontier models
- MIT-licensed open codebase
- No free tier beyond a 14-day trial
- Per-seat cost scales with org size