Having a training set is luxury. On my last job I encountered a lot of cases where people just expected to built a magic thing from unlabeled or yet ungathered data.

I work in a consulting firm doing machine learning projects for other companies that don't know much about ML... I feel you so much !

In my job, I solve almost everything with pre-trained model + a few hours of labeling + active learning.

And what do you use for deployment and making your models usable ?

Honestly I almost always use pretrained models as the initial state and train on top of it. Has worked wonders in accuracy

So far, mlflow + docker + torchserve has been enough. Soon I'll have to implement training, active learning and maintenance in the cloud as well, which will probably require more tools.