Why n8n rather than Zapier or Make?

Hosting and ownership. Zapier and Make are hosted-only, so credentials and payloads live with the vendor. n8n can run entirely on your infrastructure and the workflows are portable JSON you own. If hosted is acceptable for your data, the others are perfectly good tools.

Can our team edit the workflows after handover?

That is the main reason we use it. Workflows are a visual graph your ops team can read and change without calling us, and any custom nodes are TypeScript that ships with the repository.

Workflow automation · Integration

Alian AI for n8n

AI-aware automation that lives where your ops already breathe.

As an n8n consultant, it's our default for workflow automation — self-hosted, LLM-aware, extensible. We design with n8n as the glue and Claude/GPT as the brains. Result: workflows you can audit, edit, and own.

Scope an integration →Try our AI on your problem ↑

Things we've built on n8n

Invoice + document automation pipelines
Multi-step content distribution workflows
Compliance evidence collection pipelines

How the integration actually works

We run n8n self-hosted on your infrastructure, which keeps credentials and execution data inside your boundary. n8n is the orchestration layer — triggers, branching, retries, connectors — and the model is one node among many rather than the centre of the system. For throughput, queue mode with Redis separates the main process from workers. Proprietary systems get custom nodes written in TypeScript and handed over with the repo.

What to watch for on n8n

The constraints that decide whether this ships in weeks or drags — worth knowing before you scope, whoever builds it.

Self-hosting is usually the deciding factor: Credentials for every connected system sit inside n8n. Self-hosted means they stay on your infrastructure under your key management, and execution data — which contains real customer payloads — never leaves it. For regulated clients this is the whole argument.
Model output feeding a branch needs validation: A branch that switches on model output will eventually receive output it cannot parse. Every LLM node feeding a decision should validate against a schema and have an explicit failure path. Without it, workflows fail weeks later in ways that are painful to trace.
Execution data grows faster than you expect: Full execution history is invaluable for debugging and expensive to retain forever. Set a retention policy when the workflow is built rather than after the disk fills, and decide deliberately which executions are worth keeping in full.

Questions we get about n8n

Why n8n rather than Zapier or Make?: Hosting and ownership. Zapier and Make are hosted-only, so credentials and payloads live with the vendor. n8n can run entirely on your infrastructure and the workflows are portable JSON you own. If hosted is acceptable for your data, the others are perfectly good tools.
Can our team edit the workflows after handover?: That is the main reason we use it. Workflows are a visual graph your ops team can read and change without calling us, and any custom nodes are TypeScript that ships with the repository.