EthosPowerAI
Why self-hosting decides this comparison
The automation platform under an AI pipeline decides how much of the pipeline you own. This site's lead capture, blog publishing and calculator exports run on nine n8n workflows on a server I control, which is the witness half of what follows; Zapier and Make I have used enough to know their shape, and the figures I quote for them are from their own published pricing and plan limits rather than from running them for a client. The distinction matters, because the case for n8n is not that the other two are bad products. It is that they are products, and a retrieval pipeline that handles a client's documents cannot run through somebody else's server.
Five things worth comparing
Self-hosting is the first dimension and, for a regulated client, the only one that is not negotiable. After that come how deeply the platform understands a language model rather than merely calling one, what it costs at the volumes an ingestion pipeline actually produces, how complex a workflow it can express before you are fighting the builder, and where the data goes while the workflow runs. Feature counts are the wrong measure on every one of those.
n8n, the one I run
n8n runs on a small VPS and handles everything from a webhook-triggered ingestion into Qdrant to a multi-step orchestration across ERPNext, Listmonk and a local model, with every execution visible in a log I can read. Its decisive feature is the code node: when a no-code block does not do what the step needs, the step becomes a few lines of JavaScript or Python inline, so the ceiling that pure no-code tools impose never arrives. For a pipeline that must template a prompt, parse a model's reply and branch on it, that is the difference between a tool and a toy.
The AI nodes
The AI nodes have moved n8n from glue to orchestration. The AI Agent node runs a multi-step task against a configurable set of tools, keeps conversation memory across a session and enforces a JSON schema on the model's output; the chain nodes cover a plain prompt-and-response, question-answering over a vector store and summarisation; the extractor nodes handle sentiment, entity extraction and classification without custom parsing. The Vector Store Tool lets an agent query Qdrant or Weaviate inside its own reasoning loop. The weak spot is the documentation, and the edge cases get worked out on the community forum rather than in the manual.
Zapier, when speed beats control
Zapier's strength is time to first result: a workflow can be running in a quarter of an hour, and with more than 7,000 integrations the connector you need is almost always there. For marketing automation, CRM sync and notifications it is still the fastest path, and nothing below should be read as a claim otherwise. The limits arrive with AI work. There is no self-hosting, execution is opaque, most plans cap a workflow at a hundred steps, and the pricing scales with task volume, so a pipeline that runs tens of thousands of tasks a month costs more each month than the server that runs n8n indefinitely. Its AI actions handle a prompt and a reply; there is no agent with tools, no vector store and no memory.
Make, the visual middle
Make sits between the two. Its scenario builder is the best of the three at making branching logic legible, and its published pricing undercuts Zapier at comparable volumes. It is still hosted only, which for a regulated client or anyone putting personal data through a pipeline settles the matter before the builder is opened. Its HTTP module and JSON parsing are strong enough for custom model calls, but without code nodes or an agent primitive every AI step is a hand-built request with no memory, no tool use and no structured output.
The Verdict
Choose n8n when the data must stay on your own infrastructure, when the workflows will grow past what a visual builder can express, or when an agent with tools and memory is part of the design; it is what runs this site and what I install for clients. Choose Zapier when breadth of integrations and a fifteen-minute setup matter more than control and the workflows are simple enough to fit its limits. Choose Make for the builder and the price, where hosting elsewhere is acceptable. For an AI pipeline in a regulated business the first answer is the only one.
The workflows behind this site are drawn on the solutions page.