Applied AI
AI, in practice
Identify what matters. Automate what can be. Keep control of the rest.
Pragmatic, independent, grounded in your business
Many AI consultants start with the technology. We start with your day-to-day.
Before talking about tools or models, we sit down with your teams. We look at what they do, what takes up their time, what wears them out, and what could be handed off to a machine without losing quality. That diagnosis drives what comes next. Not the other way around.
Business first
We don't automate for the sake of it. We start from real tasks, existing workflows, actual constraints. If AI doesn't deliver measurable gains on a given process… we say so.
Full independence
We don't resell any tool, licence or platform. When we recommend something, it's because it fits your context. Not because we earn a commission.
Progress, not revolution
We start with the use case that has the most impact. We measure. We decide together what comes next. No big bang, no 90-day transformation promises.
What we actually do
Understand, then scope. Each engagement can be used alone or in sequence.
AI Audit
Find out if AI can change something in your day-to-day operations.
We analyse your workflows, identify concrete use cases and deliver a clear diagnosis: what can be automated, what can't, and where to start.
The deliverable is an operational diagnostic note. Not an 80-page report that nobody will read.
For: Executives and team leaders looking for initial clarity without heavy commitment.
AI Scoping Workshop
Lay the foundations for a concrete AI project.
A collaborative workshop with stakeholders. We identify the priority use case, define the required data, constraints, the right approach and next steps.
The deliverable is an actionable scoping brief. Not a strategy document that ends up in a drawer.
For: Teams that have identified a need but don't know how to structure it.
Not sure where to start? The AI audit is designed for that: we identify concrete use cases and tell you where to begin.
Discuss your situationAI and DAM: two topics, one thread
If you manage a DAM, you've probably seen AI features appear in your platform: auto-tagging, semantic search, metadata suggestions. That's the vendor's doing. On paper, it looks promising.
In practice… auto-tagging at 90% accuracy means 10,000 errors across 100,000 assets. And the problem is that AI doesn't raise its hand when it gets it wrong. To find those 10,000 errors, you have to check all 100,000. 90% accuracy doesn't mean 90% of the work is done. Far from it.
We don't do auto-tagging. We make sure your vendor's tagging works properly.
Prepare your DAM for AI
Are your metadata, thesaurus and governance up to the level required for your platform's AI to produce reliable results? If not, we fix that before activating anything.
Evaluate your vendor's AI features
Not all AI features are useful everywhere. We sort through them: what to activate, what to configure, what to ignore. And we measure what actually works.
Supervise AI tagging
Your vendor's auto-tagging is switched on, but who's checking? We set up quality control: sampling, precision metrics, correction loop.
Who works with us
Different profiles, one thing in common: moving forward concretely, not buying a promise.
The executive who wants clarity
They hear about AI everywhere, they see competitors moving, but they don't know where to start or who to trust. The AI audit is made for this.
The team leader losing time
Document sorting, report compilation, follow-ups, data entry… they know it could be automated but don't know how to go about it.
The organisation using AI without a framework
Teams are using ChatGPT, Copilot or other tools daily, but nobody has set the rules. A proper scoping is needed before it becomes a problem.
Frequently asked questions
Do we need technical skills to work with you?
No. We work with business teams and decision-makers, not developers. If technical skills are needed for implementation, we handle it or point you to the right people.
How long does an engagement last?
From a short diagnostic to several weeks of support. We can start with an audit to validate the opportunity before committing to a longer project.
Will AI replace our teams?
No. AI automates repetitive tasks so your teams can focus on what requires judgement and expertise. The goal isn't to cut headcount, it's to free up time for higher-value work.
Let's talk about your AI challenges
A 30-minute conversation, no strings attached, to understand your situation and see if we can help. No sales pitch, no tool demo.