Haha - well hopefully coming from a FAANG you've got some monetary runway at last :)

Some more feedback

I'm a fairly fast typist (~120 wpm) so I didn't dig too deep into your tool, but I did see that you seem to have a metric around highlighting for letters where people might be making mistakes.

You might already be doing this, but my back-of-the-envelope thought is that you really don’t want to think about typing in terms of individual letters; you want to think in terms of clusters. Ideally, you’d use some kind of frequency corpus or Markov model or something similar to break text into commonly occurring constituent clusters, e.g. the -ing in a gerund.

It's essentially the equivalent of "memory chunking" but applied to typing analysis. That’s not to say letter-level analysis is not useful (especially for hunt and peckers learning where the keys are) but as the person progresses, you’d want to introduce this idea of statistical feedback on common sequential clusters.