Kubeflow

Kubeflow is a "Kubernetes-native ML toolkit" designed to simplify deployment, management, and scaling of machine learning workflows on Kubernetes clusters.

While a platform rather than generative AI, its "AI Developer Tools" classification reflects its role in orchestrating complex AI/ML operations.

It enables "orchestration of ML workflows on Kubernetes," standardizing building, training, and deploying ML models.

Key features include "multi-framework support" (TensorFlow, PyTorch, scikit-learn), robust "pipelines" for end-to-end ML lifecycle management, plus tools for hyperparameter tuning and model serving.

Kubeflow provides a scalable, comprehensive cloud-native ML platform, helping data scientists and ML engineers manage production ML workflow complexity, accelerating AI application development and deployment in distributed environments.