METHOD AND SYSTEM FOR IDENTIFYING ROOT CAUSES

1 . A system for identifying a root cause, the system comprising a computing device, wherein

the computing device is designed and configured to:

receive a user input from a user client device;

extract at least a symptom datum from the user input, wherein the extraction of the symptom datum comprises;

generate at least a query using the at least a user input; and

generate the at least a symptom datum as a function of the at least a query;

train a machine learning process with an expert input training set wherein the expert input training set further comprises prognostic data correlated to causal link data;

assign weights, as a function of the at least a symptom datum, to the correlated data;

identify root causes as a function of the assigned weights; and

display the root causes to the user.

2 . The system of claim 1 , wherein the extracting the symptom datum further comprises using natural language processing.

3 . The system of claim 1 , wherein the computing device is further configured to extract prognostic labels from the symptom datum.

4 . The system of claim 1 , wherein the computing device is further configured to correlate prognostic labels to the expert input training set as a function of the machine learning process.

5 . The system of claim 4 wherein the computing device if further configured to assign weights to the correlated data as a function of the prognostic labels.

6 . The system of claim 1 , wherein the computing device is further configured to identify a causal link as a function of the assigned weights.

7 . The system of claim 6 , wherein the computing device is further configured to transmit the causal link to an advisor client device.

8 . The system of claim 1 , wherein the user input is a voice input.

9 . The system of claim 1 , wherein the computing device is configured to use neural networks to identify root causes as a function of the assigned weights.

10 . The system of claim 1 , wherein computing device is further configured to correlate the at least a symptom datum to the root causes as a function of the machine learning process.

11 . A method of identifying a root cause, the method comprising:

receiving, by a computing device, a user input from a user client device;

extracting, by the computing device, a symptom datum from the user input wherein extracting the symptom datum comprises:

generating at least a query using the at least a user input; and

generating the at least a symptom datum as a function of the at least a query;

training, by the computing device, a machine learning model with an expert input training set from an expert knowledge database wherein the expert input training set further comprises prognostic data correlated to causal link data;

assigning weights, by the computing device, to the correlated data as a function of the at least a symptom datum;

identifying, by the computing device, root causes as a function of the assigned weights; and

displaying, by the computer device, the root causes to the user.

12 . The method of claim 11 , wherein the extracting the symptom datum further comprises using natural language processing.

13 . The method of claim 11 , wherein the method further comprises extracting, by the computing device, prognostic labels from the symptom datum.

14 . The method of claim 11 , wherein the method further comprises correlating, by the computing device, prognostic labels to the expert input training set as a function of the machine learning process.

15 . The method of claim 14 , wherein the method further comprises, by the computing device, assigning weights to the correlated data as a function of the prognostic labels.

16 . The method of claim 11 , wherein the method further comprises, by the computing device, identifying a causal link as a function of the assigned weights.

17 . The method of claim 16 , wherein the method further comprises, by the computing device, transmitting the causal link to an advisor client device.

18 . The method of claim 11 , wherein the user input is a voice input.

19 . The method of claim 11 , wherein identifying, by the computing device, root causes as a function of the assigned weights further comprises using neural networks.

20 . The method of claim 11 , wherein the method further comprises, by the computing device, correlating the at least a symptom datum to the root causes as a function of the machine learning process.