Enterprise generative artificial intelligence architecture

A system comprising:

• one or more processors;
• and
• memory storing instructions that, when executed by the one or more processors, cause the system to perform:
• managing, by an orchestrator, a plurality of agents to generate a response to an input, wherein the orchestrator employs one or more multimodal models to process or deconstruct a prompt into a series of instructions for different agents, wherein each agent employs one or more machine-learning models to process disparate inputs or different portions of an input associated with the prompt;
• instructing, by the orchestrator, retrieval requests related to the input to the one or more agents of the plurality of agents;
• receiving, from the one or more agents of the plurality of agents, data from multiple data domains based on instructions from the orchestrator;
• analyzing, by the orchestrator, the received data to formulate one or more responses to the prompt, wherein the orchestrator provides additional retrieval requests to the one or more agents to retrieve additional data to satisfy a context validation criteria associated with the input;
• wherein the orchestrator generates intermediate instructions associated with the additional retrieval requests to the plurality of agents, wherein the intermediate instructions comprise portions of the input, questions about the input generated by the one or more multimodal models, and follow-up questions about answers generated by the one or more multimodal models;
• and
• wherein at least one agent of the one or more agents instantiates a tool to perform one or more operations on the instruction, the retrieved data, and the intermediate instructions;
• and
• outputting, by the orchestrator based on the intermediate instructions and the one or more operations performed by the tool, a validated response of the one or more responses to the input that satisfies context validation criteria and a portion of data retrieved by the one or more agents related to the input.

A non-transitory computer readable medium comprising instructions that, when executed, cause one or more processors to perform:

• managing, by an orchestrator, a plurality of agents to generate a response to an input, wherein the orchestrator employs one or more multimodal models to process or deconstruct a prompt into a series of instructions for different agents, wherein each agent employs one or more machine-learning models to process disparate inputs or different portions of an input associated with the prompt;
• instructing, by the orchestrator, retrieval requests related to the input to the one or more agents of the plurality of agents;
• receiving, from the one or more agents of the plurality of agents, data from multiple data domains based on instructions from the orchestrator;
• analyzing, by the orchestrator, the received data to formulate one or more responses to the prompt, wherein the orchestrator provides additional retrieval requests to the one or more agents to retrieve additional data to satisfy a context validation criteria associated with the input;
• wherein the orchestrator generates intermediate instructions associated with the additional retrieval requests to the plurality of agents, wherein the intermediate instructions comprise portions of the input, questions about the input generated by the one or more multimodal models, and follow-up questions about answers generated by the one or more multimodal models;
• and
• wherein at least one agent of the one or more agents instantiates a tool to perform one or more operations on the instruction, the retrieved data, and the intermediate instructions;
• and
• outputting, by the orchestrator based on the intermediate instructions and the one or more operations performed by the tool, a validated response of the one or more responses to the input that satisfies context validation criteria and a portion of data retrieved by the one or more agents related to the input.