My initial take is that if you're generating synthetic data to train up something then either you'll need to spend some time to make sure that your fake data ha

My initial take is that if you're generating synthetic data to train up something then either you'll need to spend some time to make sure that your fake data has the critical properties of the real data or you'll be able to do something really simple and easy to code up. Either way, it's not really something to outsource. If there's a lot of work necessary to understand the data, you need to do it yourself and not offload it to some remote service (or worse, expose your data/metadata to a third party). If there's not a lot of work necessary, just do it yourself, it'll be faster (there's a reason nobody's putting out things like https://en.wikipedia.org/wiki/A_Million_Random_Digits_with_100,000_Normal_Deviates https://en.wikipedia.org/wiki/A_Million_Random_Digits_with_1... anymore)