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Two founders, the strength of a whole team.

We do not just use AI: we built our own layer on top of the models. It takes on the research, the drafts, the code and the checks, and multiplies what Roland and Maxime can do. So we go further in our thinking, and we take on projects that used to need a whole agency. You still work with us: every decision and every deliverable goes through one of us.
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Using AI vs. our AI layer

Using AI is easy. Making it reliable is the work.

The difference shows in the deliverable, not in the demo.

Starting point

Using AI tools : A blank prompt

Our AI layer : Your rules, our standards and the project’s memory

Quality

Using AI tools : Depends on who types the prompt

Our AI layer : The same standard on every deliverable

Repeatable work

Using AI tools : Explained again every time

Our AI layer : Packaged as tested skills

Exact work

Using AI tools : Guessed by the model

Our AI layer : Run as tested scripts

Mistakes

Using AI tools : Repeated from one project to the next

Our AI layer : Turned into a rule, once, for every project

After launch

Using AI tools : Stops at delivery

Our AI layer : Keeps watching your numbers and proposing

What it gives you

What it changes: more strength, more depth, one standard.

  • Strength

    Two founders, the output of a team.

    Research, drafts, variations, code and tests come out in hours instead of weeks. That is how the two of us now run projects that used to take a full agency.

  • Depth

    More time to think.

    Because execution is faster, we explore more options, test more ideas and push the reasoning further before we decide. Better choices, not just quicker ones.

  • Standard

    One standard, everywhere.

    The same design rules, code conventions, accessibility and SEO checks apply to every page, app and automation, whoever or whatever produced it.

How it runs on a project

Four steps, the layer at every one.

The same method for an app, an internal tool, an automation, an AI agent or a website.

  1. Step 01

    Diagnose

    We map your tools, processes and numbers, and agree on what is worth building.

    The AI layer

    Reads your exports, tools and call notes; maps every process.

    Roland & Maxime

    Decide what to build, what to drop, and in what order.

    You get

    A costed roadmap and the criteria we will measure.

  2. Step 02

    Design

    Flows, screens and data model, iterated with you until they are right.

    The AI layer

    Produces variations to compare side by side, within our design rules.

    Roland & Maxime

    Choose one direction and design it properly.

    You get

    A validated prototype and its design system.

  3. Step 03

    Build

    On clean, documented foundations, whatever we build.

    The AI layer

    Writes code, integrations and tests, and runs every check.

    Roland & Maxime

    Review each change; own the architecture and the security.

    You get

    The product in production, documented.

  4. Step 04

    Grow

    After launch, we keep improving what moves your numbers.

    The AI layer

    Watches the numbers and flags what moved, every week.

    Roland & Maxime

    Pick the next actions by effort and impact, and ship them.

    You get

    A weekly report and a prioritised backlog.

Inside the layer

What sits between the model and your project.

  • 01

    Written standards

    Design system, code conventions, tone, accessibility and SEO rules.

  • 02

    Skills

    Audits, QA, reports and migrations as tested recipes.

  • 03

    Scripts

    Anything exact runs as code, the same every time.

  • 04

    Project memory

    Decisions and context, kept across the whole project.

  • 05

    Checks before release

    Tests, accessibility, links and speed, on every change.

The layer runs inside Dashly, our client portal.

Discover Dashly

In numbers

What clients get out of it.

50+

companies trust us

5/5

on Google reviews

+282%

Google clicks for Crealo

1

contact person, call to delivery

FAQ

Questions about our AI layer.

Another question?

Write to us
What is the difference with just using ChatGPT?
A prompt starts from zero. Our layer starts from your rules, our standards, tested skills and the project’s memory, and every result is checked before it reaches you.
Which models do you use, and can we use ours?
Mainly Claude, and the model that fits each task. If your company already approves a model or a provider, we work with it.
Can you set up the same kind of layer for our team?
Yes. We write your standards, package your repeatable work as skills, and connect agents to your tools, on your accounts.
We built a prototype with AI. Can you take it over?
Yes. We audit it first, keep what holds and rebuild what does not, to our standard.
Does it lower the cost of a project?
It lowers the cost of what used to be repetitive, and lets us spend the budget on decisions, quality and the next improvements.
How is our data handled?
On accounts you approve, with only the access each task needs. Everything is detailed on our Security page.

Let’s talk

Tell us what you want to build.

Thirty minutes with the people who will work on your project. You leave with a clear view of the scope, the timeline and the next steps.
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What happens next

  1. 1A 30-minute callWe listen to your goals, your constraints and your context.
  2. 2A clear scopeWe map what is worth doing first, and what it takes.
  3. 3A costed proposalYou decide, with no commitment and no sales pitch.