Classifiers can require a lot of examples to train correctly. You can take a decision model's outputs and apply platt scaling to arrive at a good decision boundary a lot faster.

Eventually, yes, it makes sense to move to a pure classifier model as it's probably a lot cheaper. But then you need to learn how to serve your own classifier model correctly. Compute costs are being driven up by demand to serve models and unless you're careful it's easy to use your GPUs less effectively than a company specializing in serving a model.