Workflow automation

Let the repeating steprun in the background.

Invoicing, data entry, sending reports, notifications and checks run automatically. The process picks the tool: where the data has to stay, how many steps the workflow has and which systems it connects to make the choice.

Book a discovery call See the tool comparison

The tools we use

n8n
Make
Zapier
Airtable
Supabase
GitHub
Docker

How it is built

From the step done by handto the step running in the background.

First we work out the steps and the exceptions. Only then is the tool chosen, and the reasoning written down. Once the workflow is built, run health starts being watched.

Step 1 · We map the workflowHow many steps does this job take today?

Step 2 · The tool is chosen and the workflow builtThe reasoning is written, the workflow documented.

Step 3 · It is watched and growsRun health becomes a number.

What it can do

It takes on the stepand leaves the decision to you.

Six modules build the same skeleton: trigger, log, error queue and approval point. Because the rule is written, the outcome does not change with who built the workflow.

A repeating step, a defined workflow

Every workflow is documented with its trigger, its steps and its failure behaviour. If the person who built it leaves, whoever reads the document carries it on.

The process picks the tool

The choice looks at three measures: whether the data may leave your systems, how many steps the workflow has, and whether the systems it connects to have ready integrations. All three are measured in discovery.

Every run is logged

When the workflow ran, which record it ran on and what the outcome was are written to the audit log. Every past run is traced from that same log.

Failures land in a queue

A failed run is reported to its owner, its reason is written down and it is retried. If the retry also fails, the workflow stops and you hear about it.

Human approval can be a step

An approval step sits in the middle of the workflow: actions that are hard to undo, such as sending, paying or deleting, wait for a person.

The health of the workflow is visible

Run success rate, average duration and the number of waiting errors reach you every month. When a workflow starts slowing down, you see it in the numbers.

Choosing the tool

We do not pick the tool first,we pick it after understanding the process.

n8n runs on your own server and keeps the data in; Make is fast for visual flows; Zapier stands out for the number of ready integrations. Which one gets chosen is not a brand decision but what those three properties mean for your workflow.

The tool is chosen after the process
Every run is logged
Failures queue and get reported

Let us choose the tool together

Frequently asked

Workflow automationFrequently asked questions

It depends on the process. If the data has to stay on your own server, n8n; if it is a visual, mid-complexity flow, Make; if it is a simple connection between common tools, Zapier. The reasoning is written into the discovery report.

Because the reasoning is written down, the choice can be revisited later. Because the workflow is documented, moving it to another tool does not mean starting over; the steps and exceptions are already on record.

The failed run is reported to its owner, its reason is written down and it is retried. If the retry also fails the workflow stops and a notification goes out. A workflow never stops quietly.

n8n runs on your own server and the data does not leave. If Make or Zapier is chosen, which fields go to that service is written during the build; sensitive fields never enter a cloud flow.

Yes. The workflows sit in your account or on your server and are handed over with their documentation. When you ask for a handover, training comes with it.

Steps such as payment, sending and deletion get an approval point. The workflow stops there and waits for a person; without approval it does not continue.

One, the one that takes the most time. Keeping the scope wide delays the first live run; a second workflow opens only once the first is measured and running.

Discovery takes a week. In that week we map the steps, the exceptions and the systems to connect, and choose the tool with its reasoning. The first live workflow opens within 4-8 weeks; the range depends on the number of steps, the systems to connect and the approval points. Your own timeline is written into the discovery report.

Two things are measured during discovery week: how long the step takes by hand and how often it repeats each week. Both are measured again once the workflow is running, next to the run success rate. The number of unnoticed outages is zero, because every failed run is reported.

The tools we use