Feedback:
It seems overly complicated. You lost me when you said i have to train models? Are you assuming that software developers want to train machine learning models to do something as simple as creating some test data? In reality - I reach for tools that make things easier for me, which includes not having to read a ton of documentation, download new external tools, and things that 'just work'.
It is 100% easier for me to export a little production data to test on (and maybe sanitize), or to write a small script to generate a few users and those things I need to test. Plus - then I know exactly what I'm going to get. A lot of times, after I've done this once, it will work for a good while as well - if I do change the schema, I can add some additional data for that column, and go from there, or otherwise.
For those companies who have 'messy' fixture data - is the tool the issue? My take is that the difficulty with maintaining the data could contribute to this issue, but is also more an issue of simply bad housekeeping - e.g. rushing and not tending the garden. While your system might handle this, your system also seems to require a different skillset (e.g. specific training/knowledge) than the standard QA developer might have.
If I did use it, i'd prefer it to be much easier to use - if I could include a ruby gem, and incorporte it into the testing progress, e.g. an 'after' hook after migrating the db, that would be ideal. Then, I dont really need to know much. However, I would still be concerned about whether this is deterministically creating data or if its random?
Good luck!