Nothing creates more energy in our team than an in-depth discussion about machine learning and advanced analytics. Behind our enthusiasm, we have gradually built a robust methodology to deliver complex data-based projects. We are meticulous about what we ask from the data. Is it a prediction problem? Are we asking questions about causality? What is the link to business value? Knowing this quickly helps us define the solution space.
There is no machine learning without relevant data. We are obsessed with this point, knowing that the biggest leaps in performance come from representative, high-quality data. Establishing the feedback loop to continuously improve the models is part of this. As we gradually verify the technical feasibility and business value, we advance the solutions towards production-ready systems.
Examples of our machine learning work:
- Next-best action models
- Demand forecasting
- Set optimal prices to maximize chosen KPI
- Set optimal marketing spend to maximize revenue
- Recommender systems
- Text classification
- Information extraction from unstructured data