For AI automation, Zapier is the fastest to start, Make gives more visual control, and n8n gives the most control and the most predictable costs on complex workflows. The right choice depends less on features than on who will build and maintain the workflows, how many steps they have, and how sensitive the data is. This guide compares the three on the things that actually change the decision for a service business.
Disclosure: FlowLyt builds client systems on n8n, so we have a preference. We've tried to be fair: each fact below was checked on the vendor's own pricing page in November 2026. We don't list prices because they change often.
The short version
| Zapier | Make | n8n | |
|---|---|---|---|
| Best for | Simple automations, fast | Visual multi-step scenarios | Complex, high-volume or sensitive workflows |
| Billing unit | Tasks | Credits | Executions (one full workflow run) |
| Integrations (vendor claim) | 9,000+ apps | 3,000+ native apps | Fewer prebuilt, plus HTTP and code for anything with an API |
| AI agents | Zapier Agents (separate add-on) | AI agents | AI Agent node, MCP, human approval for tool calls |
| Self-hosting | No | No | Yes (Community Edition) |
How each one bills, and why it matters
Billing is where these tools differ most, and it's the part people discover too late.
- Zapier bills per task. In Zapier's words, "a task is counted whenever Zapier successfully completes a unit of work for you" (Zapier pricing). A workflow with five actions that runs 100 times can use hundreds of tasks.
- Make bills in credits. "Each action your scenario performs consumes a certain number of credits," and some AI features can use more (Make pricing).
- n8n bills per execution. "Pricing is based on monthly workflow executions, regardless of complexity," where an execution is "a single run of your entire workflow" (n8n pricing). A ten-step workflow costs the same per run as a two-step one.
What this means in practice: for short, occasional automations, the difference is small. For a lead-handling workflow that runs every time a message arrives and has many steps (classify, look up the CRM, check the calendar, reply, log, notify), per-step billing grows fast, and per-run billing stays predictable.
Where AI agents fit
All three now support AI agents: workflows where a language model decides which step to take next instead of following a fixed path.
- Zapier Agents is sold as an add-on and billed in "activities," separately from tasks.
- Make lists AI agents among its products, and notes that features using its AI provider may consume more credits.
- n8n has an AI Agent node and AI steps, MCP client and server support, and human approval for tool calls: the agent can propose an action (like booking or refunding) and wait for a person to approve it.
That last point matters for service businesses. An agent answering customers should never be able to take an irreversible action without a rule or a human check behind it.
Integrations: count vs. coverage
Zapier's 9,000+ integrations are a real advantage when you use niche apps and don't want to touch an API. Make covers 3,000+ native apps. n8n has fewer prebuilt connectors, but any tool with an API can be connected with its HTTP node or a code step, which is how most custom business systems end up being connected anyway.
The useful question isn't "how many apps?" but "does it connect to the three or four systems my business actually runs on?" Check your calendar, CRM, messaging channel and payments before choosing.
Control, data and hosting
- Zapier and Make run in the vendor's cloud. That's convenient: no servers to maintain.
- n8n can run in n8n's cloud or on your own server with the self-hosted Community Edition. Self-hosting means your data stays on infrastructure you control, which some clinics, law firms and finance businesses prefer. It also means you're responsible for updates, backups and security.
Which one should a service business choose?
- Choose Zapier if you need a few simple automations this week, you'll build them yourself, and volume is low.
- Choose Make if you want to build multi-step scenarios visually and like seeing exactly what each step does.
- Choose n8n if your workflows are long, run often, touch sensitive data, or need AI agents with human approval, and you have someone (in-house or a partner) to set it up properly.
Whatever you choose, design for failure from day one: what happens when an API is down, a message is ambiguous or the AI isn't sure. Logging, retries and a clear handoff to a person are what separate an automation you can trust from one you have to watch.
How we use n8n at FlowLyt
Our AI lead response agent runs on n8n: it answers on WhatsApp and web chat, qualifies the inquiry, checks the calendar, books the appointment and hands your team anything that needs a person, with every step logged. If you want that built around your business instead of assembling it yourself, see the AI lead response agent.