AgentScope vs Dust

Detailed side-by-side comparison to help you choose the right tool

AgentScope

🔴Developer

AI Agents

Open-source multi-agent platform from Alibaba's DAMO Academy for building LLM agents with visual workflows and runtime management.

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Starting Price

$0

Dust

AI Agents

Dust review 2026: enterprise AI platform from Paris for building governed agents grounded in Slack, Drive, Notion — features, pricing, pros, cons.

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Starting Price

Free for 14 days

Feature Comparison

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FeatureAgentScopeDust
CategoryAI AgentsAI Agents
Pricing Plans2 listed plans3 listed plans
Starting Price$0Free for 14 days
Key Features
  • • Multi-agent framework with actor-style message passing
  • • Visual Studio for drag-and-drop agent workflows
  • • Built-in tools for memory, retrieval, code execution and computer use
  • • Visual app builder for designing multi-step LLM workflows without code
  • • Managed retrieval-augmented generation (RAG) with semantic search over connected data
  • • Multi-model support across GPT-4, Claude, Mistral, and other LLMs

AgentScope - Pros & Cons

Pros

  • ✓Same primitives in the SDK and the visual Studio — no rewrite when going from prototype to production
  • ✓Distributed runtime is a genuine differentiator vs single-process frameworks
  • ✓Native MCP client means existing MCP servers plug in with no glue code
  • ✓MIT/Apache licensing makes it safe for commercial and on-prem deployment

Cons

  • ✗Studio Cloud is still beta — managed hosting is not yet a turnkey option
  • ✗English documentation trails the Chinese-language docs in spots
  • ✗Smaller third-party ecosystem than LangGraph or CrewAI
  • ✗Distributed runtime adds operational complexity teams may not need for small agents

Dust - Pros & Cons

Pros

  • ✓Strongest sovereign / EU data story among enterprise agent platforms — important for regulated European buyers
  • ✓Per-source permission inheritance from connected systems prevents accidental information leakage
  • ✓Model-portable: a single agent can switch among Claude, GPT, Gemini, Mistral without rebuilding

Cons

  • ✗Per-seat enterprise pricing requires a sales conversation — no public price calculator
  • ✗Smaller integration catalogue than Microsoft Copilot or Glean for very large/heterogeneous IT estates
  • ✗Agent quality depends heavily on connected-source quality; messy Notion or Drive content produces messy agents

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