Jev created accessible/programmatic ergonomics around a general purpose classifiers, and did it very well; ie intuitive api and structured data approach.

Anyone can copy that and apply to an array of models - stripped down LLMs or already slim/highly performant traditional classification architectures (just wrap inference with an api that inputs/outputs the same structured data).

Jev, I think, would say their advantage is the intelligence of their models and training data including calibration: https://medium.com/code-applied/calibrated-classifiers-makin... (which i still struggle with in the general application... there's no free lunch with these things).