Published Online:July 2026
Product Name:The IUP Journal of Computer Sciences
Product Type:Article
Product Code:IJCS020726
DOI:10.71329/IUPJCS/2026.20.3.20-30
Author Name:Palli Bhaskara Rao and Ch Roopa Devi
Availability:YES
Subject/Domain:Engineering
Download Format:PDF
Pages:20-30
The paper presents a legal document analyzer and lawyer connect system, an AI-powered platform designed to simplify legal document analysis and provide intelligent assistance. The system performs document summarization, clause extraction, risk assessment, and case type prediction using a retrieval-augmented generation (RAG) pipeline. It also integrates a document-aware chatbot and a basic lawyer recommendation module to improve usability. The proposed system leverages local large language models executed via Ollama and uses ChromaDB for semantic retrieval, ensuring that responses are grounded in document context while maintaining full data privacy. The system operates entirely offline, eliminating dependency on cloud services and reducing operational costs. Experimental results demonstrate that the system provides accurate and structured insights with practical response times on CPU-based hardware. This work contributes to improving legal literacy and accessibility by providing a cost-effective and privacy-preserving AI solution for legal document analysis.
Legal documents such as court judgments, contracts, and agreements are often lengthy, complex, and written in formal legal language, making them difficult for nonexperts to understand.