About the Project
Legal RAG System is a specialized platform for legal document analysis, combining vector search with language models to transform how professionals interact with legal repositories. It addresses challenges in legal research, language complexity, and information extraction.
The system processes various document formats, extracts structured information, and transforms text into searchable vectors. Its semantic search capabilities find documents based on conceptual similarity rather than exact matches.
The RAG approach ensures generated content is grounded in legal sources, maintaining accuracy critical in legal applications. Features include case summarization, contract analysis, and legal research assistance, organized into knowledge graphs revealing relationships between concepts.
Built With
Development Journey
The Legal RAG System was developed combining expertise in legal informatics and artificial intelligence, prioritizing accuracy and security. Key phases included:
Requirements Gathering (8 weeks): Consulting legal professionals to understand workflow challenges and ethical requirements for system design.
Architecture Development (10 weeks): Creating document processing pipelines for legal texts with specialized NLP modules for citation extraction and entity recognition.
AI Model Development (12 weeks): Fine-tuning language models on legal corpora for domain-specific understanding across practice areas.
Testing included rigorous validation by legal experts to ensure outputs meet professional standards and comprehensive security audits for client confidentiality.