Summary
Used machine learning and natural language processing to convert global patent documents into structured knowledge graphs for semantic search. Replaced complex manual keyword queries with faster, more accurate prior-art and freedom-to-operate analysis. Continuously ingested and updated global patent data to keep results current. Improved research efficiency, consistency, and cost-effectiveness for enterprises, law firms, and patent offices.