Abstract: A system for using generative AI to automate electronic communication responses includes receiving, from an initiating entity, an electronic communication at a receiving entity. The system provides the electronic communication to a large language model (LLM). The system provides instructions to the LLM, causing the LLM to evaluate the electronic communication to determine whether a meeting is requested, to produce a meeting indicator, to evaluate the electronic communication to determine if there are one or more tasks, to produce a task list, and to produce a responsive electronic communication based on user-defined rules. The system receives a dataset from the LLM. If a meeting is requested, the system identifies mutually available meeting times between the initiating and receiving entities. The system sends a meeting invitation at a mutually available meeting time. The system sends the responsive electronic communication. The system generates the tasks from the task list.

Abstract: A process of determining a sentiment score from a response from at least one individual regarding a status of a project that includes receiving a first numerical rating regarding the status of the project from a first individual of the at least one individual, receiving a first textual description regarding the heath of the project from the first individual, determining a first textual score dependent upon the first textual description with the first textual score being a numerical representation of the first textual description, and aggregating the first numerical rating and the first textual score to determine a first sentiment score reflective of the status of the project by the first individual.