Dust vs AgentScope

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

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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🔴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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Custom

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Feature	Dust	AgentScope
Category	AI Agents	AI Agents
Pricing Plans	8 tiers	146 tiers
Starting Price
Key Features	• 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

✓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

✗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

✓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

✗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

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