System and method for providing analytics and intelligent question-answering via interactive dashboard

1 . A method for providing analytics and intelligent question-answering via an interactive dashboard, comprising the following steps:

receiving user input data via the interactive dashboard;

identifying user intent from the user input data using a Large Language Model (LLM);

converting the user intent into an application programming interface (API) call of a local system for the local system to proceed;

obtaining a response of the API and analyzing the response of the API using the LLM to interpret the result and generate a revised interactive dashboard representing a structured analytic context;

dynamically regenerating, based on the structured analytic context, a revised layout and content of the interactive dashboard including updated data visualizations, query paths, and control elements to facilitate two-way communication and provide real-time interactive analytics for at least one of planning, operation automation, optimization, resource orchestration, or debugging; and

presenting the natural language response and the revised layout via the interactive dashboard;

after presenting the natural language response and the revised layout, receiving, via the interactive dashboard, a further user request to generate a graph showing top correlated controller metrics; and

in response to the further user request, generating and presenting, via the interactive dashboard, the graph showing the top correlated controller metrics.

2 . The method according to claim 1 , further comprising a step of: repeating the steps until the user intent is satisfied through dynamic updates to the interactive dashboard and the natural language responses provided by the LLM.

3 . The method according to claim 1 , further comprising a step of: determining whether the user input data should be processed locally or remotely by the LLM or an associated Natural Language Processing (NLP) application.

4 . The method according to claim 1 , further comprising a step of: determining whether the user input data is product related for processing by the LLM to generate product-specific insights on the interactive dashboard.

5 . The method according to claim 1 , wherein the user intent is identified locally or remotely by a natural language processing application that includes or interacts with the LLM.

6 . The method according to claim 1 , wherein the natural language response is translated locally or remotely by a natural language processing application that includes or interacts with the LLM.

7 . The method according to claim 1 , wherein the interactive dashboard is connected to the local system which includes a natural language processing application with the LLM, or interacts with a natural language processing application with the LLM remote from the local system.

8 . The method according to claim 1 , wherein the user input data is received via a natural language interface provided by the local system or integrated with the local system, via a voice-enabled device, or via a chatbot application that is enhanced by the LLM.

9 . The method according to claim 1 , wherein the revised interactive dashboard provides information to perform planning, operation automation, optimization, resource orchestration, and debugging by dynamically presenting relevant data and insights.

10 . The method according to claim 1 , wherein the natural language response is generated by an artificial intelligence (AI) large language model (LLM).

11 . A system for providing analytics and intelligent question-answering via an interactive dashboard, comprising:

a processing module, configured to process user input data via the interactive dashboard;

an identifying module, configured to identify user intent from the user input data using a Large Language Model (LLM);

a translating module, configured to convert the user intent into an application programming interface (API) call of a local system for the local system to proceed, obtain a response of the API and analyze the response of the API using the LLM to interpret the result and generate a revised interactive dashboard representing a structured analytic context;

a dashboard generating module, configured to dynamically regenerate, based on the structured analytic context, a revised layout and content of the interactive dashboard including updated data visualizations, query paths, and control elements to facilitate two-way communication and provide real-time interactive analytics for at least one of planning, operation automation, optimization, resource orchestration, or debugging; and

a user interface connected to the dashboard generating module, configured to present the natural language response and the revised layout via the interactive dashboard, wherein, after the natural language response and the revised layout are presented, the user interface is further configured to receive, via the interactive dashboard, a further user request to generate a graph showing top correlated controller metrics, and the dashboard generating module is further configured to generate and present, via the interactive dashboard, the graph showing the top correlated controller metrics in response to the further user request.

12 . The system according to claim 11 , further comprising a converting module, configured to convert the user intent into an application programming interface (API) of the local system for the local system to proceed.

13 . The system according to claim 11 , further comprising a determining module, configured to determine whether the user input data should be processed locally or remotely by a natural language processing application that includes or interacts with the LLM.

14 . The system according to claim 11 , wherein the identifying module is remotely connected to the local system.

15 . The system according to claim 11 , wherein the translating module is a natural language processing application with the LLM which is locally or remotely connected to the local system.

16 . The system according to claim 11 , wherein the user input data is received via a natural language interface provided by the local system or integrated with the local system, via a voice-enabled device, or via a chatbot application that is enhanced by the LLM.

17 . The system according to claim 11 , wherein the revised interactive dashboard provides information to perform planning, operation automation, optimization, resource orchestration, and debugging by dynamically presenting relevant data and insights.

18 . The system according to claim 11 , wherein the natural language response is generated by an artificial intelligence (AI) large language model (LLM).