Build and ship production ML pipelines faster: a pipeline library with an optional self-hosted visual layer for modular, reproducible workflows, local testing, and experiment tracking.

Small on-prem machine learning ecosystem for small-data environments, where fast iteration, maintainability, and reliable deployment matter more than large-scale infrastructure.

Shared development toolbox for engineers. Provides reusable data + modeling pipelines and a unified packaging/deployment client for ml-deployment-ecosystem. Not for storage of models/data or high-frequency production extraction.