AI & machine learning
How do we get AI from proof of concept into production?
Most AI initiatives fail not on the model but on everything around it: data, maintenance and ownership. We take it from proof of concept through a working MVP into production, with a model that can be maintained and is explainable where it matters. A model nobody can maintain is not a result.
When do you need this?
Most AI initiatives fail not on the model but on everything around it: data, maintenance, ownership. We take it from proof of concept through MVP into production.
- From proof of concept to production
- Models that can be maintained
- Explainable where it matters
What happens if this is left alone
- Forecasts are made on experience while there is enough history to measure it, and experience is poor at spotting a break in a trend.
- A model that does get built but is not maintained quietly gets worse: the world changes and the model does not.
- Without an explanation of why a model says something, nobody uses it, and for decisions about people you are not allowed to.
Through which route do we deliver this?
The same field runs through different routes. Which one fits depends on the scope and duration of what is on the table.
Frequently asked questions
Why does our pilot never reach production?
Usually because the pilot ran on a dataset prepared by hand. In production that data has to arrive by itself every day, and that is data engineering, not model work.
What does explainable mean?
That you can say why the model reaches an outcome, in terms a user or regulator follows. For decisions about people that is not a luxury but a requirement.
Who maintains the model afterwards?
Your own team, with documentation and monitoring we put in place while building. A model that stays dependent on whoever built it is a risk you are left with.
When is machine learning not the answer?
When a fixed rule does the job. Many questions are better solved with a clear agreement or a simple calculation, and then a model is only extra maintenance.
Are you a professional working in this field? Then have a look at the roles we fill and our vacancies.
The image on this page was generated with AI. What you see is an illustration and not a photograph of our reality.
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