1. A non-transitory computer-readable medium embodying a program executable in at least one computing device, the program, when executed by the at least one computing device, causes the at least one computing device to at least: train a plurality of first machine learning models with a plurality of communications between a plurality of users and a plurality of service clients, each of the plurality of communications linked to an action implemented by at least one of the plurality of service clients; train at least one second machine learning model to recognize an intended action of a user based at least in part on a set of selections of user intents by individual ones of a plurality of service representatives; receive a natural language input from a client device; provide the natural language input and context data associated with the client device to the trained plurality of first machine learning models to generate a plurality of outputs, each of the plurality of outputs corresponding to a respective one of a plurality of possible intents representing a possible intended action to be performed by the program; select an intent for the natural language input from the plurality of possible intents based at least in part on an application of the at least one trained second machine learning model to the plurality of outputs of the plurality of trained first machine learning models and a plurality of business logic rules to the plurality of outputs of the plurality of trained first machine learning models, the intent representing an intended action to be performed by the program; determine, based at least in part on the intent and the context data, a first state in a workflow progression; change the workflow progression from the first state to a second state based at least in part on the intent and the context data; and provide to the client device a response to the natural language input, wherein the response is based at least in part on the second state in the workflow progression.