Deploy ML models and experiments at scale.
Familiar frameworks, unprecedented support
Seldon helps your data science team move faster and reduce the bottlenecks between POC and production. Our open-source machine learning deployment platform, built on Kubernetes and other cloud-native technologies, goes far beyond serving models.
With Seldon, you have the freedom to package and serve models built in any ML tool using powerful inference graphs that streamline the creation of dynamic experiments and ensembles. There are a broad range of ML pipeline configurations, so we engineered Seldon to work seamlessly with Kubeflow and CI/CD to support “GitOps”methodologies.
Agnostic & independent
Support agile workflows between data scientists and devops teams using your preferred tools
Faster to market with real-world feedback on the impact of models on KPIs makes happier engineering team
The platform does the heavy lifting, letting data science teams focus on delivering projects