Agentic artificial intelligence with domain-specific context validation
An agent-based website search interface utilizes a multimodal model to enhance enterprise operations. Data agents collect and process diverse inputs, while an orchestrator manages these agents. The system leverages machine learning models to generate insights and automate decision-making processes. It includes tools for data visualization and validation, ensuring accuracy and reliability. By integrating generative AI, the interface provides advanced search functionalities, improving user experience and operational efficiency. This facilitates seamless interaction to answer context specific questions from complex data, offering a robust solution for enterprise-level search and analysis.
1 . A method for generating a domain-specific response, the method comprising:
in response to a prompt, identifying one or more relevant domains for the prompt based on contextual information;
managing, by an orchestrator, a system of agents to generate responses to the prompt, the orchestrator employing one or more multimodal models to process or construct a series of instructions for different agents, wherein at least one agent relates to a particular domain of the one or more relevant domains based on the contextual information and wherein one or more of the multimodal models include a plurality of types, each type representing a different object and at least one type including the contextual information;
combining the responses from the system of agents, wherein combining the responses comprises performing one or more context validation processes for the particular domain and generating an aligned response that satisfies one of the one or more context validation processes for the particular domain; and
returning the aligned response in response to the prompt.
2 . The method of claim 1 , wherein each particular domain is associated with context validation criteria.
3 . The method of claim 2 , further comprising scoring the responses from the system of agents to rank the responses based on the context validation criteria.
4 . The method of claim 1 , wherein a particular validation process of the one or more context validation processes for the particular domain further comprises:
cross-referencing the generated responses with one or more domain-specific databases to determine accuracy or relevance; and
applying domain-specific rules with heuristics to improve consistency of each of the generated responses in view of the determined accuracy or relevance.
5 . The method of claim 1 , wherein generating an aligned response for the particular domain further comprises:
utilizing a domain-specific machine learning model to generate a rationale for the aligned response with sources citations from the particular domain.
6 . The method of claim 1 , wherein the context validation process for the particular domain further comprises:
incorporating feedback from one or more domain data sources to iteratively improve response accuracy.
7 . The method of claim 1 , wherein combining the responses from the system of agents further comprises preprocessing functionality to normalize the responses from the system of agents.
8 . The method of claim 7 , wherein the normalization of the responses includes one or more of handling an acronym, translating text, and managing punctuation.
9 . The method of claim 1 , wherein the generation of responses by the system of agents further comprises formatting output from each agent into a standardized format which includes converting the data into a natural language summary that is compatible with the output of other agents of the system of agents.
10 . The method of claim 1 , wherein each agent of the system of agents further comprises a feedback mechanism to iteratively update response quality.
11 . A system comprising:
one or more computer systems; and
one or more storage devices communicatively coupled to the one or more computer systems, wherein the one or more storage device store instructions that, when executed by the one or more computer systems, cause the one or more computer systems to perform operations for generating a domain-specific response, the operations comprising:
identifying one or more relevant domains for a received prompt based on contextual information;
managing, by an orchestrator, a system of agents to generate responses to the prompt, the orchestrator employing one or more multimodal models to process or construct a series of instructions for different agents, wherein at least one agent relates to a particular domain of the one or more relevant domains based on the contextual information and wherein one or more of the multimodal models include a plurality of types, each type representing a different object and at least one type including the contextual information;
combining the responses from the system of agents, wherein combining the responses comprises performing one or more context validation processes for the particular domain and generating an aligned response that satisfies one of the one or more context validation processes for the particular domain; and
returning the aligned response in response to the prompt.
12 . The system of claim 11 , wherein the operations further comprise:
scoring the responses from the system of agents to rank the responses based on context validation criteria associated with a particular domain.
13 . The system of claim 11 , wherein a particular validation process of the one or more context validation processes for the particular domain further comprises:
cross-referencing the generated responses with one or more domain-specific databases to determine accuracy or relevance; and
applying domain-specific rules with heuristics to improve consistency of each of the generated responses in view of the determined accuracy or relevance.
14 . The system of claim 11 , wherein generating an aligned response for the particular domain further comprises:
utilizing a domain-specific machine learning model to generate a rationale for the aligned response with sources citations from the particular domain.
15 . The system of claim 11 , wherein the context validation process for the particular domain further comprises:
incorporating feedback from one or more domain data sources to iteratively improve response accuracy.
16 . The system of claim 11 , wherein combining the responses from the system of agents further comprises preprocessing functionality to normalize the responses from the system of agents.
17 . The system of claim 16 , wherein the normalization of the responses includes one or more of handling an acronym, translating text, and managing punctuation.
18 . The system of claim 11 , wherein the generation of responses by the system of agents further comprises formatting output from each agent into a standardized format which includes converting the data into a natural language summary that is compatible with the output of other agents of the system of agents.
19 . The system of claim 11 , wherein each agent of the system of agents further comprises a feedback mechanism to iteratively update response quality.
20 . A non-transitory computer readable medium comprising machine readable instructions that are executable by one or more processors to:
identify one or more relevant domains for a received prompt based on contextual information;
manage, by an orchestrator, a system of agents to generate responses to the prompt, the orchestrator employing one or more multimodal models to process or construct a series of instructions for different agents, wherein at least one agent relates to a particular domain of the one or more relevant domains based on the contextual information and wherein one or more of the multimodal models include a plurality of types, each type representing a different object and at least one type including the contextual information;
combine the responses from the system of agents, wherein combining the responses comprises performing one or more context validation processes for the particular domain and generating an aligned response that satisfies one of the one or more context validation processes for the particular domain; and
return the aligned response in response to the prompt.
21 . The non-transitory computer readable medium of claim 20 , wherein a particular validation process of the one or more context validation processes for the particular domain further comprises:
cross-referencing the generated responses with one or more domain-specific databases to determine accuracy or relevance; and
applying domain-specific rules with heuristics to improve consistency of each of the generated responses in view of the determined accuracy or relevance.