S/03 · Data & AI
Data analytics and AI, in production
We used maths, algorithms and AI on ourselves before selling them. Now they turn your data into decisions, in months.
Plenty of data, few answers
The data is there, scattered across systems that don’t talk. Every report takes days, and when it lands the numbers don’t match from one department to the next.
Then there’s AI: everyone talks about it, someone already bought a licence, nobody quite knows what to do with it. The problem stays put, with one more invoice.
- 01
Data foundations
We collect, clean and connect the data you have, so it becomes one reliable source.
- 02
Analytics and dashboards
Clear indicators for decision-makers, updated without copy-paste.
- 03
Models and algorithms
Forecasts and optimisation built on your data, not on textbook examples.
- 04
Applied AI
We put AI inside real processes, where it saves time. Not inside a demo.
- 01
WE STEP IN
A fast assessment of your data and the systems it comes from. We pick the use cases worth doing and set a date.
- 02
WE BUILD
We put data flows, models and dashboards into production ourselves. No prototype left to gather dust.
- 03
WE MEASURE
We compare results with the metrics agreed at the start. If a model doesn’t move the numbers, we tell you. Then we decide the next cycle.
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What if our data is a mess?
Then that’s where we start. Cleaning up data is part of the job, not a prerequisite. The assessment tells us what can be done right away.
Does our company really need AI?
Not always. We’ll tell you during the assessment, before building anything. If solid analytics is enough, that’s where we stop.
Will our team be able to use what you build?
That’s part of delivery. We work with the people who’ll use the tools and models, and train them if needed. A solution nobody uses isn’t a solution.