claimed

Why we included this project

Data scientists who live in Jupyter notebooks often hit a wall when it's time to ship their models. CLAIMED's C3 compiler automates that step: it takes Jupyter notebooks and Python or R scripts, wraps them in container images with all dependencies installed, and emits Kubeflow pipeline components and Kubernetes job configs that a CI/CD pipeline can trigger. So the research side keeps working in their usual environment while ops gets a reproducible path without hand-writing Dockerfiles or YAML. The grid compute parallelization is the standout feature, spreading AI workloads across heterogeneous compute, and the MLX backend tracks the data and models involved, plus job records, so you can trace what went into a run. Teams on Kubeflow or OpenShift who want to close the gap between research code and production will find this useful.