I think Zapier's NLA solution goes in a similar direction and as far as I know, they are running their model on the server side to adjust workflow input and output of workflows to the unique needs of an LLM model. They are doing an amazing job there and I am also currently working on improving this (e.g. adjusting to a model's token limit).

Besides that, Lemon Agent focuses on providing an out-of-the-box agent that is great at solving tasks with workflow automation. If you want to use Zapier NLA you have to rely on generalistic agents like LangChain's ReAct Agent or the Plan and Execution Agent or you have to build your own agent. In any case, you have to twist the agent a lot to reach a certain degree of accuracy and reliability.