New Releases, Enhancements, Changes + Arize in the News!


Performance Insights by Slice View

Arize users can now immediately identify their model's worst-performing slices using our new Performance Impact panel, and understand the impact each slice has on their model at-a-glance. From the Performance Insights panel, users can click into their worst-performing slices to easily compare their slice's performance to other feature slices for in-depth comparative analysis.

With automatically surfaced worst-performing slices, users can easily grok their most impactful slices for reduced time to resolution and improved model performance.

Learn more about performance tracing here.

Search By Feature Name

Surface features using the search bar located at the top right corner of your Performance Breakdown Chart to easily locate specific feature performance.

In the News

Introducing the Arize Trust Center

Introducing the Arize Trust Center: an interactive resource designed to help both current and potential customers and partners understand our governance, policies, and security. Learn more about what trust at Arize means and Arize's security pillars with Remi Cattaiu, CISO in our newest blog post. Read more.

Interact with the Trust Center here.

Clearcover Accelerates Model Velocity, Navigates Feature Drift, and Drives Confidence In Deployed Models

The machine learning team behind Clearcover Insurance Company’s award-winning app and the fastest claims in auto insurance moves to real-time models after implementing Arize’s ML observability platform. Learn how Clearcover is achieving improved model performance and significant time savings using Arize AI in our newest case study. Read more.

Getting Started With Embeddings Is Easier Than You Think Contrary to popular belief, machine learning is math, not magic. At some point in your ML journey, you'll need some way to “explain” your model's similarities and differences between queries. The question is: how do you do that?

Enter embeddings. In our latest blog post, Arize Data Scientist Francisco Castillo in collaboration with Chief Product Officer Aparna Dhinakaran gives a crash course on embeddings 101! Learn More.

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