Overview:
AI Legal Document Analyzer is a tool that processes legal documents using NLP techniques. It helps in summarizing contracts, identifying key clauses, and detecting potential risks in agreements.Features:
Clause Extraction: Automatically extracts important sections like liability, termination, and confidentiality.
Summarization: Generates concise summaries of lengthy legal documents.
Risk Assessment: Flags potentially risky clauses in contracts.
Search & Query Support: Users can ask questions about the document and get AI-generated answers.
Tech Stack:
NLP Models: spaCy, BERT, GPT-based models for text analysis.
Document Processing: PDF-to-text conversion using PyMuPDF or Tesseract.
Web Interface: Flask/Django for backend, React.js for frontend (if applicable).
Deployment: Docker, Hugging Face Spaces, or Streamlit for easy hosting.
This project aims to help lawyers, businesses, and individuals quickly understand complex legal documents while ensuring transparency and accessibility.
we used langchain, vectordb like chromadb to retrieve extreme long pdfs and it generate answers within a minute makes it faster retrieval and we used RAG based approach and sql lite to store the recent searches we can access it anytime novelty of the project is the approach we did is not like traditional models like key extraction approach no one did this approach in open source platforms and it uses llm along with RAG extracts the text or lines automatically one thing that makes more impressive is vectordb converts text to embeddings makes it faster retrieval instead of manual approach of reading entire text in the pdf.
