MUMBAI, India, Nov. 2 -- Intellectual Property India has published a patent application (202641127018 A) filed by Rns Institute Of Technology; Dr. Kavya N P; Dr. Vishwanath V Murthy; Hemalatha S; Malarvili S; and Indhuja M on October 25, 2026, for An Artificial Intelligence–based Risk-Aware And Domain-Restricted Legal Assistance System.
Inventors include Indhuja M; Malarvili S; Hemalatha S; Dr. Vishwanath V Murthy; and Dr. Kavya N P.
The application for the patent was published on October 30, 2026, under issue no. 44/2026.
Abstract: Abstract Disclosed is an artificial intelligence–based legal assistance system, referred to as LawEase, configured to provide domain-restricted and risk-governed legal information through a conversational interface. The system includes a legal domain classification module configured to semantically analyze user input and permit processing only when predefined legal relevance parameters are satisfied, thereby restricting non-legal or unauthorized queries. LawEase further incorporates a legal risk assessment module configured to compute a quantified legal risk score for validated legal queries based on predefined parameters including misuse indicators and legal consequence sensitivity. A controlled response generation module maps the computed legal risk score to a predefined response control state, thereby regulating response permissibility, explanation depth, and certainty phrasing. The system further includes a temporal law awareness module configured to determine the enforceability of referenced legal provisions using effective-date and amendment status information, preventing reliance on amended, repealed, or superseded laws. For complex queries, a legal query decomposition module segments the input into multiple legal sub-issues and synthesizes a structured legal response. LawEase supports a hybrid execution architecture enabling selective operation in online cloud-based mode and offline local inference mode using preloaded legal data. A legal document processing module performs clause-level extraction, risk evaluation, and temporal validation under session-isolated, non-persistent data handling. Security enforcement mechanisms ensure confidentiality and system integrity, while optional multilingual support enables adaptation of legal outputs without altering legal meaning.
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