Model observability for
Fraud detection
Get in minutes what used to take years to build.
Simple, customizable, scalable, secure, ML monitoring.
Just select the data quality metric that you need to monitor or build a custom integrity metric for your use case.
Just select the data quality metric that you need to monitor or build a custom integrity metric for your use case.
Customize your drift metrics from a-z – distance functions, features, datasets, timeframes, sensitivity, and much more.
Build any bias metric your business needs and monitor them across different protected classes and sub-groups.
Track performance continuously and analyze changes, and drill into behavior segment by segment.
Easily identify and investigate model shifts and drill down into granular data to pinpoint the root cause.
Explain model behaviors on the global, cohort, and individual decision level.
Analyze and compare versions, datasets, and production timeframes to detect changes.
Correlate and group anomalies to quickly pinpoint casualty and resolve issues before they impact your business.
Centralized model monitoring management per use case. Build segments, manage configurations, and create monitors once for multiple models.
Easily gain visibility into LLM and prompt/responce behaviors and detect drift, security issues, and privacy violations.
Try the community edition
No credit card required.
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