LLM Based Taxation Agent

Our method enhances network security, using machine learning to identify threats and reduce false alerts.

Quick Summary

Our team developed an efficient tool for extracting up-to-date and relevant rules from multiple rulebooks, delivering an impressive accuracy of over 85%. This has revolutionized the way organizations access and understand compliance rules.

The Problem

Organizations were struggling to identify and understand the most recent and relevant rules from multiple ever-evolving rulebooks,resulting in compliance failures and costly penalties.

The Solution

A promising solution was engineered using advanced Language Models (LM) and robust context-awareness capabilities to extract the latest and most relevant rules accurately from multiple rulebooks. Python was used for implementing LLMs, while React was deployed for the user interface. AWS services streamlined and facilitated rapid deployment and seamless performance.

The Outcomes

The innovative tool we created provided the following tangible benefits within a short period:

  • Accurate identification of the latest and crucial rules with an accuracy rate of over 85%.
  • A significant decrease in compliance failures and penalties.
  • Simplified rule understanding, leading toenhanced efficiency.

The Tech Stack

  • Python, for implementing LLMs┬╣
  • AWS, for speedy deployment and seamless performance┬╣
  • React, employed for building user-friendly interfaces.

Ready to Start?

Embracing the inherent uncertainties of AI project outcomes, we require a minimal, fully refundable deposit at the outset. Should the project encounter unforeseen hurdles, we guarantee a full refund. If the project advances to the Proof of Concept stage, the deposit will be discounted from the overall project cost.