I wonder if the parsing, schemas and the transformations etc. could be a starting point for an advanced neural network AI programmer. Perhaps if you could combine it with an interactive system that converts text to schemas.
For example, say you had a way (a skill?) to convert a schema to a web form. Then the AI would need to handle speech-to-schema-change such as "add a field for Middle Name". Then perhaps there is a skill to go from the web form to a save data request and another to accept the request and another to update the database schema etc.
But the AI might come more in handy for interpreting more complex schemas such as nesting, grouping or workflow etc.
But besides an advanced domain specific AI it seems like this foundation of parsing, schemas and transformations would be a good start for speech-based or other higher level program generation tools. I can envision a web page that generates a CRUD application from mobile front end to Firebase back end and then spits out the code that you can then add more advanced features to.
So it seems a smart strategy to embrace open source because that can allow other developers to add mappings that you can leverage for your own app or program generation tools which you can sell.
To me the interactive web-based CRUD application generator is low hanging fruit but more interesting would be to combine your tech with a Google Duplex style interactive speech based AI programmer front end. Probably only Google and a relatively small number of companies could pull something like that off though.