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Intelligent Legal Document Assistant for Law Firms
Description
Problem:
Law firms deal with vast amounts of legal documents, case files, regulations, and precedents. Lawyers and paralegals spend significant time searching through these documents to prepare cases, find relevant precedents, or answer client queries. The manual process of combing through legal texts is not only time-consuming but also prone to missing critical information.
Solution:
Develop an Intelligent Legal Document Assistant using RAG and Azure, powered by LangChain.js, that helps law firms retrieve relevant legal documents, case precedents, and legal regulations quickly. This system can:
Search through large repositories of legal documents (contracts, case laws, legal briefs) using Azure Cognitive Search. Answer legal questions based on existing legal documents, case histories, and statutes using Azure OpenAI’s LLM (GPT-4). Summarize legal documents or provide key excerpts to streamline research for lawyers. ### Features of the Legal Document Assistant: Document Retrieval: Quickly retrieve relevant documents, legal briefs, contracts, and case laws using Azure Cognitive Search. Contextual Question Answering: Lawyers or paralegals can ask complex legal questions (e.g., "What is precedent for breach of contract in the state of New York?") and get accurate, context-based responses powered by the RAG model. Legal Document Summarization: Summarize long legal documents into concise summaries to save time in reading. Cross-Document Analysis: Allow cross-document analysis to find common patterns, terms, and case outcomes. Client Query Assistant: Allow the system to act as a client-facing chatbot to answer basic legal inquiries based on the indexed legal information.
Project Name
Intelligent Legal Document Assistant for Law Firms
Description
Problem:
Law firms deal with vast amounts of legal documents, case files, regulations, and precedents. Lawyers and paralegals spend significant time searching through these documents to prepare cases, find relevant precedents, or answer client queries. The manual process of combing through legal texts is not only time-consuming but also prone to missing critical information.
Solution:
Develop an Intelligent Legal Document Assistant using RAG and Azure, powered by LangChain.js, that helps law firms retrieve relevant legal documents, case precedents, and legal regulations quickly. This system can:
Search through large repositories of legal documents (contracts, case laws, legal briefs) using Azure Cognitive Search.
Answer legal questions based on existing legal documents, case histories, and statutes using Azure OpenAI’s LLM (GPT-4).
Summarize legal documents or provide key excerpts to streamline research for lawyers.
### Features of the Legal Document Assistant:
Document Retrieval: Quickly retrieve relevant documents, legal briefs, contracts, and case laws using Azure Cognitive Search.
Contextual Question Answering: Lawyers or paralegals can ask complex legal questions (e.g., "What is precedent for breach of contract in the state of New York?") and get accurate, context-based responses powered by the RAG model.
Legal Document Summarization: Summarize long legal documents into concise summaries to save time in reading.
Cross-Document Analysis: Allow cross-document analysis to find common patterns, terms, and case outcomes.
Client Query Assistant: Allow the system to act as a client-facing chatbot to answer basic legal inquiries based on the indexed legal information.
Technology & Languages
Project Repository URL
https://github.com/theshivay/Intelligent-Legal-Document-Assistant-for-Law-Firms
Deployed Endpoint URL
No response
Project Video
Upload Soon
Team Members
Shivam Mishra
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