Main Purpose
Superwise aims to solve model observability for high-scale machine learning (ML) operations.
Key Features
- Model Observability: Superwise provides visibility and context into the behaviors of ML models, allowing users to monitor and maintain them at scale.
- Risk Monitoring: Superwise enables users to express and monitor model risks as they relate to their business, helping them identify and mitigate potential issues.
- Intuitive Interface: Superwise offers an intuitive interface for data scientists, ML engineers, and business operations to easily observe and manage models without alert fatigue.
Use Case
- High-Scale ML Operations: Superwise is designed for organizations that have dozens, hundreds, or thousands of ML models running in production, each composed of hundreds to thousands of features. It helps them monitor and maintain these models at scale, reducing noise and alert fatigue.
- Model Risk Management: Superwise allows users to monitor and mitigate risks associated with ML models, ensuring that they align with business objectives and perform as expected.
