Chassis

Chassis is an open-source Python SDK that takes a trained ML model and emits a containerized prediction service with one function call. It supports the usual framework zoo (Scikit-learn, PyTorch, TensorFlow) and compiles for both x86 and ARM, so the same model can ship to a Kubernetes cluster, a Raspberry Pi, or an NVIDIA Jetson without re-wrapping the dependency hell each time.

The target user is the MLOps-light data scientist who can write Python and `pip install chassisml`, but doesn't want to hand-author a Dockerfile, a gRPC server, or a Kubernetes manifest just to expose a model. It is fully free and community-maintained under the modzy/chassis GitHub org, with Modzy as the original commercial sponsor; deployment to Modzy's platform is one of several supported targets (containerd, Docker, Kubernetes are all first-class).

Worth noting: Chassis is plumbing, not a model. It does not train, fine-tune, or evaluate; it solves the unglamorous packaging step. The project's release cadence has been quiet (v1.5 has been the current major for a while), so treat it as a stable utility rather than an aggressively evolving platform.