Yes! We want to make the whole ML process from training to deployment to monitoring radically more convenient. The CLI interface makes it easy to quickly train ML models without ever opening a Jupyter notebook, learning what pandas and numpy are etc. And after you’re done training, we want you to be able to incorporate your models into your existing stack: we have language libraries for programming languages traditionally underserved by the current ml tools: ruby, golang, elixir, nodejs, rust. (We also have python). All prediction happens in process with no network requests, meaning you don’t have to deploy a separate service to host your ml models :)