Superwise

Video coming soon

What do you do?

From missing values to concept drift, Superwise makes sense of models in production, so teams know when models misbehave, what happened, and what to do next. 

Superwise model observability gives you visibility and context into your models’ behaviors, so you can easily express and monitor model risks as they relate to your business and seamlessly collaborate to resolve issues. With Superwise, data scientists, ML engineers, and business ops get intuitive model observability without the alert fatigue so you can be confident about your model management and focus on the fun things in life like building newer, better models.

 

Already used by top-tier organizations, Superwise monitors millions of predictions daily, helps ML practitioners see beyond statistical noise, and focuses teams on real model issues impacting business operations across various use cases. Implemented use cases include Customer Lifetime Value (CLV) predictions, fraud detection, lead scoring, underwriting, credit risk, and more. Recognized for its innovative technology and approach, Gartner was named Superwise as a 2020 Cool Vendor in Enterprise AI Governance.

How much does it cost?

Model usage-based pricing that lets you pay as you go. 

Only pay for the models that you monitor.

Request a free trial

Video/Tutorials

Documentation

What’s a sample use case? Where can I learn from?

  • Superwise is about solving model observability for high-scale ML operations.

    Great observability needs to support high-scale, and when it comes to models, once they’re in production and business-critical, they scale like nothing else in the engineering world. A model (singular) is relatively easy to monitor and maintain. The same cannot be said when you have dozens, hundreds, or thousands of models running in the real world, each made up of hundreds to thousands of features. The amount of noise and alert fatigue that can result in is no joke.

Feature List

  • Gain full visibility

Superwise automatically discovers and computes an extensive set of metrics for each element in your training dataset and across the model production inference flow (raw data, features, inferences, label), including:

  • Activity metrics.
  • Integrity metrics.
  • Distribution metrics.
  • Drift calculations.
  • Performance metrics.
  • Monitoring policy builder
      • Leverage a wide range of existing templates, including Data drift, Data quality issues, Biases, Staleness, and more for quick monitoring setups.
      • Build any custom logic you would like to monitor.
      • Deliver violations and alerts to any communication channel and workflow you would like to trigger (Slack, New Relic, Webhook, auto-retraining, etc.)
  • Faster, more precise anomaly detection.

Superwise’s anomaly detection makes it possible to detect abnormal events automatically across different versions and subpopulations while considering seasonality and adjustments for new temporal behaviors.

  • Easy troubleshooting, faster resolution

Superwise correlates and groups anomalies into incidents to deliver a big picture overview of why models are misbehaving – giving you everything you need to quickly pinpoint casualty and resolve issues faster.

  • Platform agnostic. Model agnostic. API-first.

Superwise is an open platform – we’re model and platform agnostic and 100% 

API-first. You can access anything in Superwise with our APIs, giving you 

complete control over logging, triggering processes, and even extracting trends 

to reflect them in your organization’s BI tools.

  • Integrate in no time to your production stack
    • From any platform.
    • For any type of model.
    • Ready-made plugins for common serving platforms like Aws Sagemaker, Google Vertex, and more. 

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Summary
How much does it cost?
Video/Tutorials
What’s a sample use case? Where can I learn from?
Feature List