Dify vs Flowise

Dify's knowledge base retrieval attaches source citations to every response, letting support bots tell users exactly which document chunk answered their question.

Dify's Prompt IDE runs the same prompt against GPT-4o, Claude, and Llama side-by-side, with latency and cost comparisons surfaced in the same view.

Dify's workflow canvas supports if/else routing, loops, and code nodes, enabling pipelines like lead qualification that branch on input data without any server code.

Dify publishes any chatflow or workflow as a REST API endpoint with one click, letting backend teams integrate AI features without building their own inference infrastructure.

FlowiseChatFlow nodes chain a document loader, text splitter, and vector store on a visual canvas. A production-ready Q&A endpoint is live before the frontend team finishes their morning standup.

BufferMemory and ConversationSummaryMemory nodes plug directly into any ChatFlow, giving agents context retention across sessions without writing custom state management code.

AgentFlow chains Tool nodes (search, calculator, SQL) and exposes them via Flowise's built-in REST endpoint, reducing tool-calling integration from days to a few hours.

Flowise runs entirely on your own servers via Docker, connecting to local Ollama or LM Studio endpoints so no prompt data leaves the network.