ML.NET Lets .NET Teams Run ML Models in C# Without Python Sidecars

Software platform Mattrx replaced a Python scikit-learn microservice with ML.NET running directly inside its .NET 9 application, eliminating the need for a separate service or second programming language in production. The switch covered three core ML tasks — regression, classification, and clustering — all built and trained entirely in C#. The migration cut prediction latency from 45 ms to 2.8 ms, reduced deployment pipelines from two to one, and saved approximately $160 per month in infrastructure costs. The team argues that for common business ML use cases such as predicting values, classifying categories, or grouping data, Python expertise and a math background are not prerequisites. Their results included an R² of 0.78 for the regression model and an AUC of 0.86 for churn classification, matching the accuracy of the previous Python-based system.