Four ways in — from a first conversation about where AI fits, to rethinking a process, to building the software, to making images that didn’t exist a moment ago.
AI is impressive. Making it useful is the interesting part.
Not sure where AI fits into your business? Let’s find out.
I help businesses understand the opportunities, evaluate technologies and identify practical ways to get started. We look at real challenges, existing workflows and the people who work with them.
Sometimes the result is a straightforward AI application. Sometimes it’s a clearer understanding of what not to do. Both can save a surprising amount of time.
From initial AI assessments and prompt engineering to tool evaluation, practical guidance and responsible AI adoption.
How it usually goes
Teams that suspect AI could help but don’t know where to start — or started somewhere and want a clear second opinion.
Too many tools, vague use cases, a pilot that never left the pilot phase, or simply no time to look into it properly.
We talk about real work: what takes time, where things get stuck, who is involved.
I look at workflows, data and constraints and evaluate which applications are realistic — and which aren’t.
A short list ordered by effort and expected benefit. Including the things that are better left alone.
One concrete first move you can start with. With me, or without me.
A clear picture, a prioritised shortlist and a first step.
Same challenge. Better process.
Some business processes were designed around limitations that no longer exist. Others just happened. And somehow, they stayed.
I help businesses rethink manual, time-consuming workflows and turn them into smarter, AI-driven ways of working.
That starts with understanding what actually happens today, questioning assumptions and describing what a better process should achieve.
From there, we explore technologies, develop concepts and design solutions that fit the organisation. Not everything needs to be automated. Sometimes we need to reconsider why we’re doing it in the first place.
Process analysis, target-process design, AI concepts and an implementation roadmap.
How it usually goes
What really happens today — observed, not assumed. Every hand-off, every copy-and-paste.
Where time, quality and patience get lost, and why the process works the way it does.
What the process should achieve — described before any tool is chosen.
Where AI genuinely helps, where simple software is enough, and where people decide.
Steps in a sensible order, small enough to test and learn from.
How we will know it works: agreed upfront, checked afterwards.
A rethought process, a realistic roadmap and criteria to judge it by.
There’s probably a tool for that. But is it the right one?
Sometimes the best solution is something designed specifically for the way a business works.
I develop tailored applications and complex software systems, combining established software engineering with AI-assisted development.
From requirements and architecture to interfaces, integrations and deployment.
AI has changed how software can be built. It hasn’t made clear requirements, technical judgment or good architecture obsolete. Quite the opposite.
Requirements, architecture, interfaces, integrations, deployment.
How it usually goes
What exactly needs solving — and whether software is the answer at all.
What should be different once it runs. Concrete, testable, agreed.
Users, data, constraints and the edge cases nobody mentions in the first meeting.
A structure that fits the problem, the team and the next five years — not the latest trend.
Established engineering, accelerated by AI-assisted development, reviewed by a human.
Connected to the systems that already exist, shipped properly, and kept alive.
Software that fits the way you work — and someone who understands why it was built that way.
Making things that didn’t exist a moment ago.
Generative AI has opened up entirely new possibilities for visual content, communication and creative production.
I work with AI image and video generation, prompt engineering and creative workflows — from developing visual concepts to creating more consistent and scalable approaches to content production.
My experience in Fashion Tech has given me a close-up view of what happens when generative technologies meet real creative production requirements.
And sometimes, experimenting is the whole point.
Visual concepts, image and video generation, prompt engineering, creative workflows.
How it usually goes
What the image should do and say — written down before anything is generated.
Exploring directions quickly, keeping what works, dropping what doesn’t.
Making the tenth image belong to the first: light, style, character, detail.
Turning a good result into a process a team can use again.
Rights, disclosure and where generated content should not be used.
Clear visual intent, consistent results and a workflow your team can repeat.
Data doesn’t become useful just because someone put it into a dashboard.
I explore how AI can help structure information, identify patterns, support analysis and make complex datasets easier to work with.
The interesting part isn’t generating more numbers. It’s asking better questions of the ones we already have.
Powerful technology deserves thoughtful use.
Privacy, information security, transparency and human oversight aren’t obstacles to innovation. They’re part of making innovation sustainable.
I help businesses approach AI with an understanding of its capabilities, limitations and risks. Because being able to do something isn’t always a good reason to do it.
No guaranteed AI ROI, no automation for its own sake. Every engagement starts with a conversation about the actual problem.
Tell me what you’re working on. We might find a straightforward solution. We might discover something more ambitious. Either way, a good conversation is a good place to start.
Start a conversation