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How we turn data into value.

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Our workflow.

We typically implement both a learning and scoring pipeline. This holds for machine learning systems, but also for cluster models, NLP systems, lookalike detectors, anomaly detectors, etc.

The learning pipeline 'learns' how to transform data into a desired result.

Example: a neural network is trained to predict propensities to churn.

The scoring pipeline applies the transformation into the desired result.

Example: the trained neural network actually predicts propensities to churn.

Both can run as often as you like, whenever you like.


We are motivated AI-consultants, eager to help you.

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