Application Orchestration: Dust allows developers to define complex LLM workflows through a visual interface or code, combining multiple model calls, data processing steps, and logical judgments into a complete application.
Multi-Model Support: Dust is not tied to a single model provider; it supports models from multiple sources such as OpenAI, Anthropic, Google, etc. Developers can choose the most suitable model according to their needs.
Data Management: Dust provides data storage and retrieval functions, supporting AI applications that require external knowledge bases such as RAG (Retrieval-Augmented Generation).
Deployment and Scaling: Dust handles model deployment, scaling, and monitoring, allowing developers to focus on application logic rather than infrastructure.