I remember a lib that was like this but would use GANs etc to gen data. I tried it with little success, reverting to SMOTE. Wonder how this would do? My impression is that tabular data is difficult to use synthetically.
That being said, synthetic data definitely isn't a magic pill for all use cases. I have found it particularly useful for things like QA, performance testing, etc. -- where alternative tools for test data creation aren't sufficient.
For the use case of imbalanced classification: May be worth asking what is it about existing solutions (SMOTE) that doesn't work well?