Hello Hugging Face forum members,
my name is Mislav, I’m a recent computer science graduate from Croatia. I had the idea of building Grammarly for Croatian Google Chrome plugin. I want to pursue that idea, but before I do that, I want to have a roadmap of what I would have to do in order to build it.
I am completely new to NLP and don’t have any experience with NLP, but I do have some basic experience with machine learning.
Here are the features that I want to build (in order). There will probably be others later on:

Spell checker
Tone detector - tells the user how does the text sound - confident, formal, informal etc.
Improvements suggesstor - suggests how the user can improve his/her text so that it resembles a certain tone better (i.e. how to make his/her message seem more formal)

I don’t know how Grammarly works - what does it use as a technology to detect grammar errors? What does it use to predict sentiment? What does it use to measure how engaging is the text? How does it judge the delivery of the message intended by the text? Essentially, if you had to reverse-engineer Grammarly and use that knowledge to help me build it, I’d be grateful.
I’m doing this project to both learn about NLP and ship the product, so ideally I could have a balance of learning & speed while working on this project. Maybe I could reuse some code from the Hugging Face repo? I intend to make the product a freemium product, so I’m not sure if that’s aligned with the code license.
Any suggestions as to how to go about building this would be appreciated. Again, I am new to this, so a  detailed description would go a long way.
Best,
Mislav