Legal AI Co-pilot: Turning Public Case Law into a Conversational Research Tool

Legal research in India traditionally means manually digging through High Court and Supreme Court judgments — long, unstructured documents scattered across public court websites, with no easy way to search, filter, or extract the specific details a case demands. For a legal research startup looking to build a modern product around this data, that meant solving for:

• Case law published as unstructured public documents, with no centralized or queryable format
• No efficient way to search or filter cases by outcome, party, court, or case type
• Legal professionals needing to read entire judgments manually to extract relevant facts — court, verdict date, parties, nature of dispute
• No way to interact with case law conversationally, forcing users into slow, document-by-document research

Tenafor built the platform end-to-end, from raw data collection through the user-facing product:

• Web scraping pipeline to collect publicly available case data from High Court and Supreme Court websites
• Structured data extraction, parsing raw judgments into organized case details — court, verdict date, case number, petitioners, respondents, and nature of dispute
• A RAG (retrieval-augmented generation) pipeline feeding structured and full-text case data into an LLM, enabling accurate, source-grounded responses
• A conversational chat interface letting users query case law directly in natural language, rather than manually reading full judgments
• Search and filtering tools, letting users narrow cases by outcome (e.g., "For," "Against," "Others") and other case attributes
• A clean, structured case view surfacing the key facts of a judgment at a glance — court, dates, parties, and dispute details

Tenafor delivered a full-stack AI research product that turns dense, unstructured legal judgments into a searchable, conversational knowledge base:

• Legal research time reduced significantly, replacing manual document review with direct, conversational queries
• A structured, growing database of case law built from public court sources
• A chat-based research experience that lets legal professionals get straight to relevant facts and precedents
• A scalable data pipeline that can expand to cover additional courts and case types over time