Published February 3, 2026
Library
graduated
TADkit: Time-series Anomaly Detection Kit with Interactivity and Tools
PythonPackage
Maintainer:IRT-SystemX
Description
A toolkit integrating and wrapping all anomaly detection components with a possibility to: interact between the various components (preprocessing, engeering, modeling) interact with a visualization/annotation tool (e.g. Debiai) via an API intended for expert-in-the-loop iterations
Owner:IRT-SystemX
Keywords:tadkit-core
CONTEXT
Anomaly detection is a major challenge in artificial intelligence, as it enables
the automatic identification of unusual or suspicious patterns in data, which is
essential both for ensuring the reliability of systems and for preventing risks in
critical domains such as cybersecurity, healthcare, or industrial maintenance
VALUE PROPOSITION
Anomaly detection is a major challenge in artificial intelligence, as it enables
the automatic identification of unusual or suspicious patterns in data, which is essential both for ensuring the reliability of systems and for preventing risks in critical domains such as cybersecurity, healthcare, or industrial maintenance
WHEN TO USE IT
It shall be used both during the training and the production step to monitor data.
RESOURCES
