Fan Li, a Principal Data Scientist at DuPont, discusses how his company uses Neo4j graph technology to develop a competitive intelligence platform. The platform aims to provide fast, quality, and deep insights for scientists, engineers, and business users. DuPont's mission is to deliver sustainable and innovative solutions to solve some of the world's greatest challenges. The company has diversified its business into various industries such as nutrition, health, industrial bio-sciences, safety, protection, and chemical manufacturing. Due to the diverse data sources and end-users, DuPont needed a platform that could ingest large amounts of data from external sources and provide clear connections for users with overarching missions. They initially attempted using SQL but found it challenging due to schema limitations and flexibility issues. Neo4j was introduced as an alternative graph database solution, which offered native graph technology, a vibrant open-source community, and flexible data schema. The benefits of using Neo4j include its natural flow for mapping data sources into entities and relationships, easy analysis by end-users, and flexible data schema. DuPont uses Neo4j to build a graph-based platform that includes publications, patents, government funding, and other business data. The platform provides features such as search engines, alert systems, dashboards, interactive analysis, reporting, and self-service analysis using BI tools. The company aims to expand its knowledge base with internal technology data, enable end-users to incorporate their personal knowledge and insights, develop advanced features like recommendations, and incorporate other technology areas. Ultimately, the goal is to connect scientists, engineers, and external collaborators to deliver innovative solutions.