01. n8n implementation

n8n in production. Not n8n on a laptop.

Most n8n deployments hit a wall at production: auth, scale, integrations, AI nodes that need real model engineering. We stand n8n up correctly, integrate it with your existing stack, and operate it long-term.

Schedule a call →Start a diagnosticReplies within 1 business day

02. The problem

n8n is the breakout. The deployment is the wall.

n8n is the breakout workflow automation tool of 2026. Open source, self-hostable, AI-native, fairly priced. Most teams stand it up and hit production reality: auth, scale, governance, integration with non-n8n systems, AI nodes that need real model engineering, eval discipline.

From there it's one of two paths. Limp along on a deployment that works for the obvious workflows and breaks at the edge. Or migrate off, citing "scale issues" that were really integration and operations issues.

The tool isn't the problem. The deployment is. Production n8n needs the same operational substrate as any other piece of business-critical software. Eval suites, audit logs, RBAC, error budgets, observability.

03. What we do

Stand it up. Integrate. Govern. Operate.

Stand it up

Self-hosted n8n on infrastructure that scales. Or n8n Cloud, configured correctly.

Integrate

Custom n8n nodes for your internal systems. AI workflow nodes built on Claude with eval suites and HITL.

Govern

Auth, RBAC, audit logs, error budgets, observability from day one.

Operate

Long-term ownership or handoff to your team with the documentation to maintain it.

04. Why us

Production engineering on the n8n + Claude stack.

15⁺

YEARS OPERATING

Phoenix & Los Angeles studio. Software for operations since 2010.

25⁺

ENGINEERS ACROSS TWO TIMEZONES

Senior team, EST/PST coverage, no offshore tier. Built to embed.

n8n + Claude

PRIMARY AI ORCHESTRATION STACK

AI engineering depth across both surfaces. Orchestration and judgment, one team.

05. How we approach it

Same n8n. New ground floor.

The pattern repeats. A workflow that started in n8n, hit production scale, and needed the substrate to run. The work below is the architecture we ship every time, anonymized.

UNDETECTED DRIFT EVENTS POST-EVAL DEPLOY

REPRESENTATIVE N8N ARCHITECTURE

Production n8n with eval-graded AI nodes

Starting state: n8n Cloud, fifteen workflows, three of them depending on an LLM node configured with a hand-tuned prompt and no eval coverage. The AI nodes worked until they didn't. Drift went undetected for two weeks because there was no test harness, no audit log of model outputs, and no HITL gate on the write path that posted to NetSuite.

What we shipped: custom nodes for their ERP, an eval suite for the AI decision nodes that ran on every prompt or model change, and a HITL gate on every destructive write. Audit log on the model side, RBAC on the n8n side, observability tied to SLOs the business actually cared about. Same n8n. New ground floor.

See selected work →

06. How we engage

Diagnose. Build. Embed.

01 · Diagnose

Assess your n8n deployment or candidate workflows.

Six weeks. We assess your existing n8n environment (or the workflows you'd start with), score them for production-readiness, and hand you a sequenced build plan.

Start a diagnostic →

02 · Build

Production n8n with custom nodes, eval suites, and governance.

Twelve-week sprints. We stand up the environment, build custom nodes for your internal systems, integrate AI workflow nodes, and ship to production.

Scope a build →

03 · Embed

Long-term operation of your n8n environment.

We operate it. Or we hand it off to your team with the documentation, runbooks, and eval discipline to maintain it. Both are options.

Talk about embedding →

07. FAQ

Common questions, straight answers.

Why n8n instead of Zapier or Make?

n8n is self-hostable (data stays in your control), AI-native, and priced for production scale. Zapier is excellent for small workflows; n8n is the right choice when workflows are core to your operation.

We've already deployed n8n. Why hire you?

Most of our n8n clients had already deployed it. We come in when the workflows are real but the production substrate isn't, when n8n is doing the work but auth, governance, eval, and integration are still ad hoc.

Do you build custom n8n nodes?

Yes. Most production n8n deployments need at least one or two custom nodes for internal systems that don't have a stock integration. We build them as part of the engagement.

How do you handle AI nodes in n8n?

We treat them like any other production AI: eval suites in CI, HITL gates on destructive actions, audit logs, error budgets. The n8n workflow is the orchestrator; the AI work is engineered separately. See how we build Claude into production for the model side.

Can you migrate us off Zapier to n8n?

Yes. That's a common Build engagement. We rebuild your workflows in n8n, integrate them with systems Zapier couldn't reach, and add the engineering substrate.

What's the relationship to Claude?

Claude is the model we standardize on for AI nodes, tool use, MCP, long context, eval-friendly output. n8n orchestrates; Claude does the judgment work. More on how we build with Claude.