LawHaven - An AI Driven Legal Assistance Platform

Abstract

Access to legal information and professional legal guidance remains a major challenge for individuals, small businesses, and underserved communities in India. Traditional legal research platforms and consultation systems are expensive, time-consuming, and often require expert interpretation. This research introduces LawHaven, an AI-powered, multilingual legal intelligence platform designed to provide accessible, real-time legal assistance using advanced Natural Language Processing (NLP) and Retrieval-Augmented Generation (RAG). The system integrates AI-driven modules including case prediction, personalized legal advisory, case summarization, similar-case retrieval, legal dictionary lookup, and English-to-Kannada translation. The platform is powered by a curated and continuously updated knowledge base containing the Indian Penal Code (IPC), the Constitution of India, and Supreme Court’s fortnightly case digests. The core architecture uses LangChain for model orchestration, FAISS for vector search, FastAPI for backend services, and Groq-based LLMs for generating context-aware legal responses. Experiments demonstrate that AI-driven outcome prediction and RAG-based advisory significantly improve legal research efficiency and provide explainable insights compared to existing static legal search engines. By combining real-time retrieval, domain-specific language models, and multilingual support, LawHaven enhances legal accessibility, simplifies complex legal processes, and contributes toward reducing knowledge gaps in the Indian justice system.