System

A system comprising:

• circuitry configured to:
• receive, via a communication interface coupled to a packet-switched network, natural language input information from a terminal device, apply tokenization and entity extraction to convert the input information into structured data, and analyze the structured data using a natural language processing model to identify a user intent and missing items of required parameter data;
• retrieve workflow definition information corresponding to the user intent from a storage device, generate context information embedding the workflow definition information and the missing items, and execute inference processing using a generative neural network model to generate a query sentence for acquiring the missing items;
• transmit the query sentence to the terminal device via the communication interface, receive additional input information, extract required parameter data from the additional input information, and store the required parameter data as workflow data;
• and
• complete the workflow based on the stored workflow data, transmit a completion result to the terminal device via the communication interface, and update workflow definition information based on stored record information comprising completion results and extracted parameter accuracy metrics.

A method comprising:

• receiving, via a communication interface coupled to a packet-switched network, input information expressed in natural language from a terminal device, converting the input information into a structured data format, and storing the structured data in a storage device;
• analyzing the structured data using a natural language processing model to identify a user intent and missing items of required parameter data, and retrieving, from the storage device, workflow definition information corresponding to the user intent;
• generating context information for a generative neural network model based on the workflow definition information and the missing items of required parameter data, executing inference processing using the generative neural network model with the context information as input to generate a query sentence for acquiring the missing items, and transmitting the query sentence to the terminal device via the communication interface;
• receiving additional input information from the terminal device in response to the query sentence, extracting required parameter data from the additional input information using the natural language processing model, and storing the required parameter data as workflow data for progressing the workflow corresponding to the user intent;
• and
• completing the workflow based on the stored workflow data and transmitting a completion result to the terminal device via the communication interface.