NLP monitoring

Bring structure to unstructured data. SUPERWISE® connects with Elemeta to turn messy NLP inputs into clear, traceable metafeatures you can track, visualize, and act on—fast.

Easily extract NLP metafeatures

Elemeta

Elemeta is an open-source Python library that transforms raw text and image data into structured, tabular metafeatures—ready for monitoring. With its clean Python API, it plugs seamlessly into SUPERWISE, helping you track NLP signals, surface drift, and monitor model behavior with clarity.

Contextual metrics

I want to monitor average values for SentimentPolarity in all social pipelines across all segments & entire set

SUPERWISE uses contextual metafeatures from Elemeta to track changes in user input or model output—so you can detect spikes, drifts, and outliers before they impact production.

Statistical metrics

I want to monitor max value for OutOfVocabularyCount in video search model across teens segment

Use statistical metafeatures to track shifts in population, spot underperforming segments, and catch subtle changes in data distribution—before they chip away at model accuracy.

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community edition account.

				
					!pip install superwise

Build your project

				
					import superwise as sw
project = sw.project("Fraud detection")
model = sw.model(project,"Customer a") 
policy = sw.policy(model,drift_template)

Start monitoring

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