Conversational artificial intelligence system with multi-agent orchestration and parallel supervisory processing

Abstract

A conversational artificial intelligence system includes a plurality of large language models configured to perform different functions. A routing system routes requests to a large language model best suited for a task associated with the request. A conversation manager coordinates a flow of a conversation between the system and a user using the plurality of large language models. A supervisory module operates in parallel with the conversation to audit responses generated during the conversation and provides feedback that contributes to construction of downstream responses to the user. One or more safety modules prevent the system from performing actions that are outside of defined constraints. The routing system may route requests based on latency requirements, domain, or classification tasks, and may fail over to a different large language model when a first large language model degrades.