Eurybia

github.com/MAIF/eurybia AI Infrastructure & MLOps Open-source projectOpen source

Eurybia tracks model drift and validates data during machine learning model deployment.

github.com/MAIF/eurybia
Eurybia homepage screenshot

About Eurybia

Eurybia is an open-source Python library from the MAIF GitHub project for monitoring model drift over time. It helps you check data before a model goes into production. You pass a baseline or training dataset and a current or production dataset as pandas DataFrames, and you can add a deployed model and encoder. The usual workflow declares a SmartDrift object, compiles it, and generates an HTML report. It installs with pip and is intended for Python 3.9 to 3.12.

Pricing is not clearly stated.

Key features

  • Feature importance, scatter plot and dataset distribution views
  • AUC evolution and model performance evolution views
  • Predicted value distribution comparison between baseline and newest data
  • HTML reports that can be shared with non-data users
  • Installs with pip
  • Optional deployed model and encoder for richer report content
Best for: Data scientists and data analysts who monitor drift and validate data before deploying models.
Watch out for
  • Model and encoder results need datasets the model can use
  • Intended for Python versions 3.9 to 3.12

Eurybia at a glance

Type
Open-source project
Pricing
Not confirmed. Check the site
Details verified
Oct 22, 2026 · Official source
Open source
Yes · Source code
Language
English
Last checked
Oct 5, 2026 · Online when checked
Listed
Oct 5, 2026

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