Legal Assist using LLM and RAG
UK research data on legal proceeding sample using LLM and RAG on azure stack
Project Title: Investigating the Application of Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) on UK Research Data for Legal Proceeding Samples on Azure Stack
#Project Overview This project aims to explore the utilization of Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) in analyzing UK research data on legal proceeding samples. By leveraging the capabilities of Azure Stack, this project seeks to demonstrate the effectiveness of these advanced language models in facilitating the examination and comprehension of legal proceeding data. #Objectives
Investigate the application of LLMs and RAG: Examine the suitability and potential benefits of employing LLMs and RAG in analyzing legal proceeding samples.
Analyze UK research data: Utilize UK research data on legal proceeding samples to demonstrate the capabilities of LLMs and RAG in this context.
Leverage Azure Stack: Deploy and manage the project infrastructure on Azure Stack, ensuring scalability, security, and reliability.
#Expected Outcomes
Improved understanding of LLMs and RAG: Gain insights into the strengths and limitations of LLMs and RAG in analyzing legal proceeding data.
Enhanced data analysis capabilities: Develop and demonstrate the effectiveness of LLMs and RAG in facilitating the examination and comprehension of legal proceeding data.
Azure Stack deployment expertise: Acquire hands-on experience in deploying and managing project infrastructure on Azure Stack.