n8n vs Flowise in 2025: Building AI Agents and Chatbots Compared
Both n8n and Flowise let you build AI agents and RAG chatbots visually, and both are open-source and self-hostable — so which should you use in 2025? The short answer: Flowise is a specialist for LLM app-building, while n8n is a generalist that does AI plus everything else your automation needs to touch. Here's how to choose.
Specialist vs generalist
Flowise is purpose-built for LLM applications on top of LangChain and LlamaIndex. If your entire goal is a sophisticated RAG pipeline or agent — with fine-grained control over chains, retrievers, and memory — Flowise exposes those primitives deeply and cleanly.
n8n includes robust AI-agent and vector-store nodes too, but inside a full automation platform. The AI is one part of a workflow that can also hit your CRM, send WhatsApp messages, write to a database, and run on a schedule. For most business use cases, the AI is a step — not the whole app.
Integrations and what happens around the model
A chatbot is rarely just a chatbot. It needs to capture leads, log conversations, check live inventory, escalate to a human, and notify a team. That surrounding orchestration is exactly where n8n's 400+ integrations shine — the model is wrapped in real business actions.
Flowise can call external tools, but connecting to the long tail of business systems is more work than in n8n, where those integrations are native nodes. If your agent needs to do things in the real world, n8n's breadth is a decisive advantage.
Ship a WhatsApp RAG agent on n8n
An n8n workflow: a WhatsApp AI chatbot that answers 24/7 from your company docs — RAG plus real business actions.
Get the n8n template on Gumroad →
Picking the right tool
Choose Flowise when the LLM pipeline is the product and you want the deepest possible control over chains, embeddings, and retrieval strategy — for example, an ML team prototyping advanced agent architectures.
Choose n8n when the chatbot is part of a business process: a WhatsApp support agent that answers from your docs and logs to your CRM, a lead-qualifying assistant, or a RAG bot that also triggers downstream automations. For teams shipping AI into operations, n8n's all-in-one nature usually wins.
Final thoughts
Flowise is the right pick when the LLM chain itself is the whole job; n8n is the right pick when the AI has to live inside a real workflow with integrations, logging, and escalation. For most businesses, that's n8n.
Ready to automate? Skip the build.
This exact workflow is packaged, documented, and ready to import into your n8n instance.
