Methods and systems for responding to prompts related to financial events

A server system, comprising:

• a communication interface;
• a memory comprising executable instructions;
• and
• a processor communicably coupled to the communication interface and the memory, the processor configured to cause the server system to at least:
• determine, by a Large Language Model (LLM) associated with a server system, a prompt intent based, at least in part, on a prompt from a user, the prompt intent indicating an intent of the user;
• determine a prompt type of the prompt based, at least in part, on the prompt intent, the prompt type comprising at least one of a factual prompt, a reasoning prompt, or a combination prompt;
• identify, by the LLM, one or more prompt attributes associated with the prompt, the one or more prompt attributes indicating information describing one or more financial events associated with an entity;
• extract relevant information associated with the entity from a database based, at least in part, on the prompt intent, the prompt type, and the one or more prompt attributes;
• generate, by the LLM, a prompt response based, at least in part, on the relevant information and the prompt intent, the prompt response indicating a curated response to the prompt based on the prompt type using the relevant information;
• and
• transmit the prompt response to the user.

A non-transitory computer-readable storage medium comprising computer-executable instructions that, when executed by at least a processor of a server system, cause the server system to perform a method comprising:

• determining, by a Large Language Model (LLM) associated with a server system, a prompt intent based, at least in part, on a prompt from a user, the prompt intent indicating an intent of the user;
• determining a prompt type of the prompt based, at least in part, on the prompt intent, the prompt type comprising at least one of a factual prompt, a reasoning prompt, or a combination prompt;
• identifying, by the LLM, one or more prompt attributes associated with the prompt, the one or more prompt attributes indicating information describing one or more financial events associated with an entity;
• extracting relevant information associated with the entity from a database based, at least in part, on the prompt intent, the prompt type, and the one or more prompt attributes;
• generating, by the LLM, a prompt response based, at least in part, on the relevant information and the prompt intent, the prompt response indicating a curated response to the prompt based on the prompt type using the relevant information;
• and
• transmitting the prompt response to the user.