Question 1

Can I migrate from Zapier to n8n or custom AI automation?

Accepted Answer

Yes. n8n has import patterns for common Zapier triggers but most nontrivial Zaps need manual recreation because Zapier's perstep model does not map cleanly onto n8n's node graph. Migration to a fully custom AI automation stack typically takes 2 to 6 weeks depending on the number of workflows and integration complexity.

Question 2

Is n8n reliable enough for production?

Accepted Answer

Yes, for teams with the engineering capacity to run it. Selfhosted n8n with proper Postgres, queue mode, monitoring, and backups is as reliable as any cloud service. n8n Cloud has an SLA on paid tiers. The risk is operational ownership: "free OSS" is only free when you have the team to run it.

Question 3

Now that Zapier and Make both ship AI Agents, why would I still pay for a custom build?

Accepted Answer

Because platform Agents are good at singlestep or shortchain actiontaking work. They are not good at stateful longhorizon orchestration, deep LLM observability, regressiontested prompt eval, custom retry semantics, or workflows that need to hold complex state across hours or days. The platforms also do not let you selfhost or versioncontrol the agent itself. Custom builds win when reasoning depth, observability, and unit economics at scale matter more than timetofirstdemo.

Question 4

How does MCP support compare across the three?

Accepted Answer

All three platforms ship MCP, but the surface differs. Zapier exposes Agents that consume MCP and counts each call as 2 tasks. Make's MCP Server exposes scenarios as tools to external MCP clients (Claude, Cursor, ChatGPT) and Make Agents consume MCP internally. n8n ships both directions: MCP Client Tool, standalone MCP Client node, and an MCP Trigger that lets external clients call any n8n workflow as a tool, with OAuth2 on the client. n8n's surface is the most flexible for engineers building bidirectional MCP integrations.

Question 5

When does custom AI automation pay back versus platform spend?

Accepted Answer

For teams spending $1,500+ per month on Zapier or Make and running workflows with real reasoning requirements, a custom build typically pays back within 8 to 14 months on a 24month total cost basis. Selfhosted n8n with an engineering team to maintain it can extend that payback window because perexecution cost is already near zero. The decision usually comes down to whether you need observability, eval, and orchestration depth that n8n alone cannot give you.

Question 6

What is a typical timeline for a custom AI automation build?

Accepted Answer

Small builds (singleworkflow agent, one or two integrations) ship in 4 to 6 weeks. Midcomplexity builds (multiworkflow agents, RAG, multiple integrations) ship in 8 to 12 weeks. Large enterprise builds (multiagent orchestration, regulated data, full observability stack) ship in 12 to 16 weeks. Bitontree's typical midbuild lands in the 10 to 14 week range.

Question 7

Do you build on n8n, or only fully custom stacks?

Accepted Answer

Both. When n8n is the right tool, fast iteration, selfhosted, code execution and LangChain nodes are enough, we build on n8n and harden it. When workflows need depth n8n cannot deliver, we move to LangGraph, custom orchestration, and dedicated observability. We start with a free AI Fit Assessment to decide which side of that line your workflow lives on.

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n8n vs Zapier vs Make vs Custom AI Automation: Which Fits Your Business in 2026?

Yash Vibhandik

Yash Vibhandik

Not Sure Which Automation Approach Fits Your Business?

Not Sure Which Automation Approach Fits Your Business?