Foundational Time Series Model Online Multi Series Anomaly Detector (Beta)

This endpoint performs online anomaly detection based on the provided data. It uses cross-validation for more robust detection of anomalies and it supports detection for univariate and multivariate scenarios. It takes a JSON as an input containing information like the series frequency and historical data. (See below for a full description of the parameters.) The response contains a flag indicating if the date has an anomaly, it provides the prediction interval used to define if an observation is an anomaly, and it reports the associated z-score for each point. Get your token for private beta at https://dashboard.nixtla.io.