Machine learning models degrade over time if left unchecked. This phenomenon is known as a concept drift - when predictions become less accurate over time due to unexpected changes in the real world. This can negatively affect your business KPIs and customer experience, resulting in churn.
In many cases, it is also difficult to measure the true accuracy of a model in production due to absence of labels. Because of that, less than 5% of companies that employ AI technologies have solutions to monitor the performance of their models.
Sanau ML Analytics monitors your machine learning models in production and notifies you if there are any factors that degrade their performance. It integrates into any existing infrastructure and runs either on cloud or on premises. With Sanau ML dashboard you can track all the metrics related to the health of your model.