Learning and personal data management platform

A system comprising:

• (a) at least one network interface;
• (b) at least one processing unit communicatively coupled to the at least one network interface and configured to perform a natural language query processing method, the method comprising:
• (i) obtaining a natural language query related to personal financial data of a user;
• (ii) generating query vectors comprising embeddings of the natural language query;
• (iii) matching the query vectors with document vectors generated from chunks of reference documents related to the personal financial data;
• (iv) retrieving the chunks from at least one database;
• (v) generating a response to the natural language query by inputting to at least one large language model a prompt comprising:
• (A) the natural language query;
• and
• (B) the chunks as context for use in responding to the natural language query;
• and
• (vi) providing the response to the user,
• wherein the method further comprises, prior to the obtaining of the natural language query, detecting a trigger resulting from a change in the personal financial data of the user, wherein the change comprises at least one of asset or liability values of the user as stored in the at least one database exceeding a trigger threshold, and wherein the obtaining of the natural language query is performed in response to the trigger.

A non-transitory computer readable medium having stored thereon computer program code that is executable by at least one processor, and that when executed by the at least one processor causes the at least one processor to perform a natural language query processing method, the method comprising:

• (a) obtaining a natural language query related to personal financial data of a user;
• (b) generating query vectors comprising embeddings of the natural language query;
• (c) matching the query vectors with document vectors generated from chunks of reference documents related to the personal financial data;
• (d) retrieving the chunks from at least one database;
• (e) generating a response to the natural language query by inputting to at least one large language model a prompt comprising:
• (i) the natural language query;
• and
• (ii) the chunks as context for use in responding to the natural language query;
• and
• (f) providing the response to the user,
• wherein the method further comprises, prior to the obtaining of the natural language query, detecting a trigger resulting from a change in the personal financial data of the user, wherein the change comprises at least one of asset or liability values of the user as stored in the at least one database exceeding a trigger threshold, and wherein the obtaining of the natural language query is performed in response to the trigger.