Seldon Deploy provides oversight and governance for machine learning (ML) deployments.
It is built atop leading open-source tools including Seldon Core and Alibi.
Deploy ML models easily using industry-leading, open-source projects
Ensure reproducible deployments and rollbacks with GitOps
Release models with confidence via canaries and shadows
Inspect model predictions using Alibi explainers
Apply advanced monitoring to model inferences
Seldon Core is a cloud-agnostic, open-source platform for deploying machine learning models.
Deploy models in the cloud or on-premise
Create powerful inference graphs
Unify heterogeneous ML toolkits under one serving layer
See the Seldon Core documentation for further details.
For further information, please refer to the detailed Architecture pages.
Alibi is an open-source Python toolkit for understanding models. Alibi Detect offers drift and outlier detection, while Alibi Explain provides model inspection and interpretation.
Provide high quality reference implementations of black-box ML model explanation algorithms
Define a consistent API for interpretable ML methods
Support multiple use cases (e.g. tabular, text and image data classification, regression)
Implement the latest model explanation, concept drift, algorithmic bias detection and other ML model monitoring and interpretation methods