When you see the potential of data and AI, but don't know where to start — that's exactly where we come in.
We've done this dozens of times, across different organisations, domains, and industries. E-commerce, finance, logistics, customer service. On GCP, AWS, and Azure. The starting point is always the same: your strategy, your objectives, and an honest conversation about where data and AI can actually move the needle.
Our clients value our pragmatism. We make complex things simple. We prove value fast. We don't arrive with a generic framework — we bring a sharp outside perspective, grounded in real delivery experience.
We write code, build pipelines, and ship working products. Any plan we put on the table is one we can execute ourselves. If you like what comes out of the quickscan and want help building it, you may not need to look any further.
The quickscan is run in collaboration with Berend Dumas of Dumas Data Consultancy. Berend is a data scientist and AI practitioner with a track record at bol.com across recommendation systems, large-scale algorithm work, and AI-driven content generation. Between us, we cover strategy, data engineering, and applied AI, across e-commerce, logistics, sports, and media. If what comes out of the two days requires building, you have two people in the room who have done it before.
Two days, one concrete use case
The quickscan is a focused two-day engagement. We work with you and your team, not alongside you.
Think big
We dive into your company strategy, objectives, and key results. What are you trying to achieve? Where is value created, and where is it lost? Together we map the landscape of data and AI opportunities across your business — without getting lost in technical details.
Start small
From the landscape, we identify the use case with the highest impact and the lowest barrier to start. We design it concretely: what data you need, what the output looks like, who owns it, and how you measure success. You leave with something you can actually act on.
What you leave with
By the end of the two days, you have a concrete starting point — not a strategy deck.
Opportunity map
A clear overview of where data and AI can make a meaningful difference in your business, grounded in your strategy and objectives.
First use case design
One use case, fully scoped: the business goal, the data required, the expected output, how you measure success, and what the first step looks like.
Prioritized backlog
The other opportunities, ranked. So you know what to tackle after the first use case proves its value.
Shared language
Business and data teams aligned on terminology, expectations, and what "done" looks like. This sounds small. It isn't.