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SeldonIO/seldon-core

An MLOps and LLMOps framework for deploying, managing, and scaling AI systems, from singular models to complex data-centric applications, on Kubernetes.

Core Features

Pipelines for composable AI applications with real-time data streaming via Kafka.

Autoscaling for models and application components based on native or custom logic.

Cost-efficient Multi-Model Serving and Overcommit to save infrastructure costs.

Experiments with A/B tests and shadow deployments for robust model evaluation.

Custom Components for extending functionality like drift detection, outlier detection, or LLMs.

Detailed Introduction

Seldon Core 2 is a robust MLOps and LLMOps framework designed for deploying, managing, and scaling diverse AI systems within Kubernetes environments. It enables standardized deployment of various model types, supporting both on-premise and cloud infrastructures. The platform focuses on modular, data-centric AI applications, offering features like real-time data streaming, intelligent autoscaling, and cost-efficient multi-model serving. It empowers organizations to streamline their machine learning operations, from experimentation to production, ensuring scalability and reliability for thousands of models.