Analyzing documents via a large language model, determining compliance, and generating a narrative

Abstract

Embodiments of the disclosure are directed to systems and methods for providing personalized tax recommendations using LLMs. In particular, the disclosed system can utilize an LLM embedded within a tax software system to assist with generating cohesive, actionable advice tailored to specific financial scenarios, whether for individuals or companies. The LLM can be fine-tuned and specifically trained on a knowledge base of tax data. In some embodiments, by leveraging various advanced natural language processing capabilities, the disclosed LLM can comprehend, interpret, and transform complex tax information into understandable narratives that address specific user needs. Furthermore, a feedback loop can be used to enrich the model's accuracy and relevance, such as by continuously learning from user interactions and adapting to changes in laws and regulations. This can ensure communications remain precise and highly personalized.