You are basically asking for model serving or a way to manage and deliver your models in a secure and governed way to production.
There are a few things you need to think about:
- How will my models be managed?
- How will my models be delivered (served) for inferencing?
- Do I need real-time or batch level delivery?
In its simplest form, you store or deploy the trained model to a remote repository known as a model server. Then at runtime, you retrieve the model, pass features (inputs) into it and predict.
There's a lot of value in this simple model. Firstly, your models are stored in a central repository which provides governance, share-ability, versioning and reusability. It should be as easy as a few function calls.
Secondly, retrieving the model should also be as easy as a single function call. However, you must ensure the appropriate protocols are supported and are secure.