n8n vs Make (formerly Integromat): Which Automation Builder Fits AI Workflows?

n8n vs Make: Which One Powers Your AI Strategy?

In 2026, automation is no longer just about moving data between spreadsheets. It's about orchestrating AI agents, managing LLM chains, and creating autonomous workflows. Two titans dominate this space: n8n and Make.

At a Glance: The Verdict

• Choose n8n if: You need deep AI integration, prefer self-hosting for data privacy, or require a technical, code-friendly environment for complex AI agents.
• Choose Make if: You want a sleek, visual interface, thousands of ready-to-use app integrations, and a low-maintenance cloud environment.

Key Differences in AI Capability

While both platforms support AI, their approaches differ. n8n offers a native LangChain integration, making it a powerhouse for those building RAG (Retrieval-Augmented Generation) systems. You can easily drag and drop vector stores, memory nodes, and specific LLM providers.

Make, on the other hand, excels in API-first connectivity. While it doesn't have a built-in LangChain interface as deep as n8n's, its vast library of modules for OpenAI, Anthropic, and Pinecone allows for rapid prototyping of AI-powered business processes.

Pricing and Hosting

Make follows a cloud-first, volume-based pricing model. It's easy to start but can become expensive as your execution count grows. n8n offers a unique advantage: it's fair-code and can be self-hosted, giving you unlimited executions on your own infrastructure—a massive plus for high-volume AI tasks.