Very happy to share - my co-founder and I started a company called Simiotics, where we offer metadata stores for data, preprocessing functions/transforms, machine learning models, and statistics. We also have tools that integrate with these metadata stores to automate work that most data science teams perform manually today - running preprocessing jobs, updating models in production, monitoring the distribution of data and predictions in production models, things like that.

Our pitch is that, instead of having to do complicated things like set up an Airflow cluster, spin up a Kubernetes cluster and build helm charts, manage Spark, etc., a data scientist can just call out to our APIs from their Python programs (which may be running in notebooks), and we take care of the stuff they need to do but don't want to do.

This is our website: http://simiotics.com

These are our docs: http://docs.simiotics.com (They are in a very sorry state, and it embarrasses us to post them here, but we are going to use that embarrassment to push us to make them better!)