Belgium & France
Automation agency.
Process first.
Automating a bad process doesn't fix it: it just makes it wrong faster, and harder to undo. We check first whether the task deserves to exist, then whether it's stable, and only then whether it can be automated.
Book a Discovery CallThe definition that matters
What an
automation agency
does
— and doesn't do.
An automation agency identifies a company's repetitive tasks, documents them, then has them carried out by a chain of tools instead of a person.
The difference from an integrator fits in one sentence: the integrator deploys software chosen in advance, the automation agency starts from the process and picks the tool afterwards — or concludes that no tool is needed at all.
What it shouldn't do: sell a number of automations. The deliverable isn't a workflow that runs, it's time given back to people whose job was to do something else.
Before automating anything
Three questions, in this order.
If the answer to any of the three is no, automation waits. This isn't caution — it's what separates a lasting gain from one more piece of technical debt.
Should this process even exist?
Sometimes the first answer is no. A weekly report that three people receive and none of them open doesn't need automating, it needs cancelling. An agency that never asks this question is billing you to automate your own waste.
Check: who uses the output, and to decide what?
Is this process stable?
Automating locks things in place. If the rules change every quarter, or every case is an exception, automation becomes debt: you'll have to maintain it with every change, and it'll break quietly in between. An unstable process gets documented first, automated second.
Check: how many times have the rules changed in the last twelve months?
Is the input data reliable?
This is the most common failure cause, and the least anticipated. An automation plugged into a half-empty CRM produces errors faster than a person would, and users stop trusting it after the third one. According to Gartner (February 2025), by the end of 2026 organisations will have abandoned 60% of AI projects that aren't built on data ready to use.
Check: pull a hundred random rows and count the empty fields.
In practice
What actually gets automated in SMEs.
Ranked by real-world return, not by technical sophistication. The two rankings are rarely the same.
- 01
Re-keying data between two tools
The same information typed into the CRM, then the accounting system, then a spreadsheet. Immediate gain, near-zero risk, and almost always the first project that pays off.
- 02
Follow-ups
Unanswered quotes, unpaid invoices, missing documents. Simple rules, high volume, and nobody likes doing them — the perfect combination.
- 03
Producing repetitive documents
Quotes, contracts, reports generated from a template and already-structured data. Pays off as soon as volume passes a handful per week.
- 04
Recurring reporting
Provided someone actually reads the report and acts on it. If not, see question one.
- 05
Sorting and qualifying inbound requests
Emails, enquiries, job applications. This is where AI genuinely does something a rule can't — but only after the manual process has been written down.
How to choose
Five criteria.
These apply to us as much as anyone else. If we fail on one of them, the criterion still stands — we're the ones who should be ruled out.
It starts with an audit, not a tool
If the first proposal mentions n8n, Make or Zapier before looking at your processes, you're buying tool expertise, not a transformation. The tool is an implementation detail, and it gets picked last.
It's willing to tell you not to automate
The best qualifying signal there is. An agency paid by the number of automations delivered has no reason to tell you the process should be scrapped instead.
It documents before it builds
An automation with no process map is a black box. The day it breaks — and it will — nobody will know exactly what it was doing.
It leaves you able to maintain it
At least one person on your side needs to understand how it works and be able to tweak a simple rule. Otherwise every change comes with an invoice, and that's dependency, not autonomy.
It measures before and after
How long the task used to take, how long it takes now, how many fewer errors. Without a baseline figure, there's no provable gain — just an impression.
How we work
60% preparation.
40% building.
That's the 60/40 rule, and it always surprises people at the first quote: on an automation project built to last, most of the time goes in before a single workflow is written — mapping the real process, cleaning and structuring the input data, deciding what not to automate.
An agency that quotes a price without looking at your data is only pricing the 40%. The gap shows up later, in the form of automations that get things wrong and that nobody dares touch anymore.
The diagnosis takes 14 working days, price quoted upfront. To work out where to start without us, the method is published in this article, and the groundwork stocktake in this one.
Frequently asked questions
What people ask us.
- What is an automation agency?
- It's a provider that identifies a company's repetitive tasks, documents them, then has them carried out by a chain of tools instead of a person. The distinction from an integrator is clear: the integrator deploys software chosen in advance, the automation agency starts from the process and picks the tool afterwards — or concludes that no tool is needed at all.
- How much does automating a process cost for an SME?
- It depends entirely on the process, and above all on the state of the data going in. The rule we apply is the 60/40 one: on a project that works, roughly 60% of the time goes into preparation — mapping and structuring the data — and 40% into building. An agency that prices automation without looking at your data is only pricing the 40%.
- What tools do you use to automate?
- Make, n8n, Zapier and the native automation features of whatever's already in place, depending on the case. That choice comes at the end: it depends on what your teams can actually maintain, your hosting constraints, and the real complexity of the process. Starting with the tool is the most common mistake in the industry.
- Do you need AI to automate?
- Usually not. Most of the gains in SMEs come from deterministic rules — if this, then that — which are far more reliable, cheaper and easier to debug than a model. AI earns its place when the input isn't structured: sorting emails, pulling data out of a document, qualifying a free-text request.
- How long before you see a result?
- A well-chosen first project produces a measurable result within a few weeks. If you're told it'll be months before you see any effect, the initial scope is too wide: shrink it down to a first win, which then buys the credibility for the ones after it.
- Do you work with Belgian SMEs?
- Yes. DigitalEasy is a Franco-Belgian outfit working on both sides of the border, in French. The diagnosis takes 14 working days and its price is quoted before we start.
Thirty minutes to find out what to automate first.
Free, no obligation. We'll tell you straight whether automation is your issue — and if it isn't, what is.
Book a Discovery Call