AI automation

AI automation for your business processes

AI automation means handing the repetitive parts of a workflow to intelligent systems: data entry, reporting, follow-ups, summaries. Average measured result across our clients: 7 hours saved per week per employee. AI Makers maps your processes, prioritises them by ROI, builds on n8n and Claude, then measures the gain — every system shipped to production and documented.

Book my free diagnostic

saved / week / person

+200

systems in production

+50

companies supported

An AI automation workshop with a client team — Building an automated workflow, in a workshop with the client.

Trusted by

Teams trained and systems running in production at more than 50 companies, from large groups to small businesses.

Hover a logo to read the testimonial

At a glance

What an automated workflow looks like

A trigger, an agent that processes, outputs in seconds. Here’s a real case: a lead that arrives by email, qualified and routed without a single hand touching it.

The trigger

A lead arrives by email

L’agent traite

Reads, qualifies, decides

The outputs, in seconds

CRM record created and qualified

Task assigned to the right person

Personalised reply sent

saved per week, per person

This workflow runs around the clock, with nothing forgotten and nothing copy-pasted. Your teams focus on what matters, the machine does the rest.

The processes

What actually gets automated

Six families of process show up in almost every engagement. If your teams spend hours a week on them, there’s a system to build.

Reporting

Activity reports, dashboards, weekly consolidations generated automatically from your own data.

Data entry and transfer

Document extraction, CRM updates, tool-to-tool sync, with no manual re-keying.

Follow-ups

Client, supplier, candidate or overdue-invoice reminders fired at the right moment, with the right context.

Summaries

Meeting notes, long-document digests, condensed monitoring pushed to the right people.

Onboarding

A new client or hire arrives: access, documents and checklists created with no manual step.

Invoicing

Invoice generation, payment tracking, reconciliation, and alerts on late payers.

The method

Four steps, no gamble

We never start with the tool. We start with the process and its ROI.

Mapping

We document your real workflows, task by task, with the people who run them. No assumptions.

ROI scoring

Every process gets scored: time spent, frequency, complexity, potential gain. We only build what pays back.

Build

The system is built on n8n and Claude, connected to your tools, tested with your teams, then shipped to production.

Measurement

Every system has its KPIs: real usage, time saved, errors avoided. What isn’t measured gets dropped.

Tool vs system

A tool is bought. A system is built.

Buying a ChatGPT licence for the whole team isn’t automation. It’s a tool. And a tool with no process behind it sits unused after three weeks.

A system is different: a workflow wired to your data that runs without anyone thinking about it, with tracking indicators and one person accountable for it. It survives departures, activity spikes and tool changes.

That’s why we don’t sell licences or prototypes: we ship systems to production, documented, with the intellectual property transferred to you in full.

With or without

Build these systems alone, or with us

Hire a senior AI profile, or plug in a dedicated engineer who is operational on day one. The maths is quick.

Without support

6 to 12 months to hire a senior AI expert
Uncertain ROI on projects at €150,000+
Total dependency on a single vendor
€70,000+/year in fixed salary and employer costs

With AI Makers

One offer, the same run for every client
A dedicated AI engineer, operational on day one
ROI measured from the first month, KPI by KPI
Full intellectual property, zero dependency

The stack

Our tools, no spin

We have no exclusivity with anyone. Here’s what we use and why.

n8n

Our main automation engine. Open source, self-hosted, advanced logic and a native connection to AI models. Most of our systems are built on n8n.

Claude

The AI model we use for reasoning tasks: document analysis, drafting, summarising, qualification. Wired into the workflows via API.

Make

A solid visual alternative for mid-complexity scenarios. We reach for it when the client’s ecosystem calls for it.

Zapier

The simplest way to connect two tools on a basic scenario. Its limits: cost at volume and restricted logic. Honestly, rarely our first pick for real business processes.

FAQ

Frequently asked questions about automation

Which processes should you automate first?

The ones that combine three traits: high frequency, clear rules, low human value-add. In practice: recurring reporting, data entry and transfer between tools, client and supplier follow-ups, meeting and document summaries. That is exactly what our audit measures — each process gets an ROI score before any build decision.

How long does it take to automate a workflow?

In our Build phase, a dedicated engineer ships 1 to 2 systems a month to production. A simple workflow (an automated reminder, a generated report) deploys in a few weeks. A deeper system, wired to several tools with human validation steps, takes a full cycle. The real delay is not technical: it is team adoption, which is why two hours of weekly training is built in.

n8n or Zapier?

Zapier is simpler and fine for connecting two tools on a basic scenario. n8n is more powerful: advanced conditional logic, calls to AI models like Claude, self-hosting, and cost that does not explode with volume. For serious business processes we build on n8n. But the tool is secondary: a bad process automated is still a bad process.

How do you measure the ROI of an automation?

Before the build, we baseline the starting point: time on the task, frequency, people involved, error rate. After go-live, we track the same indicators plus real system usage. ROI is counted in hours recovered and errors avoided. Across our clients the average measured gain is 7 hours per week per employee.

Do you need technical skills in-house?

Not to start: our engineer builds, documents and ships to production. Yes to last: every engagement includes two hours of weekly training and the AI Champions programme, which trains internal referents. At six months your teams run the systems without us, and the intellectual property is entirely yours.

Resources