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A generic monitoring package for machine learning models developed for Rijkswaterstaat

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The client,

Rijkswaterstaat has been responsible for the Netherlands’ roads and waterways since 1798. It is the executive agency of the Ministry of Infrastructure and Water Management. It manages and develops national roads, waterways and bodies of water, and works towards a sustainable living environment. Together with other organisations, it works to protect the country from flooding. A country with enough green space and enough clean water. And where you can travel safely and smoothly from A to B.

Client Rijkswaterstaat
Industry Government
Services AI Solutions
Tools & techniques Python, pytorch, tensorflow, Alibi-detect, Pydantic

Our solution,

Rijkswaterstaat has developed and deployed several AI models. To maintain their quality in production, these models need active monitoring for issues such as data drift and prediction drift. Manual monitoring does not scale, so a generic monitoring package is needed to detect drift and outliers. We developed a generic monitoring package for all these models.

DSL came up with an inventive solution that we can put to good use.
Nanine Overgaauw Rijkswaterstaat - SRE Data Science

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