Understand your NLP models like never before

Here are a few things that any organization deploying NLP models into production should be doing to ensure that those models continue to perform as expected.

The first-ever complete NLP monitoring solution

Identify Anomalies & Data Drift

Ensure consistency in data extraction pipelines and monitor for data drift.

Simulate "What-If" Scenarios

Interact with feature scores and observing the impact on model outputs.

Understand Your Models Better

Identify the most important features impacting predictions of your NLP models.

Monitoring & Explainability for Your NLP Models


Compare the similarity of new input documents to the documents used to train your NLP models

Bias Analytics

Detect biases in your NLP models by uncovering differences in accuracy and other performance metrics across different subgroups


Identify the specific words within a document that contributed the most to a given prediction

Thanks to Warrior, we know that our preventative care models are fair and that we can catch any potential issues before they impact our members.

– Heather Carroll Cox, Chief Data & Analytics Officer at Humana

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