Leveraging AI and Future Ready Data to Accelerate R&D

Synonymous with innovation, Research and Development (R&D) is all about competitive edge. Generative AI has emerged as an R&D catalyst, promising to unlock new use cases and unexplored opportunities to increase margins without extra spending. This includes filing patents and identifying market demands and how to capture them with existing technology. But before we can hand over scientific data to an LLM, we need to streamline its acquisition, management and access while laying a foundation for continuous innovation. Scientific data is different from other kinds of data—and unlocking its value presents unique challenges. This data’s commonly unstructured nature requires flexibility and the ability to easily accommodate evolving data models that can be used to test new ideas quickly.

Watch our expert panel of seasoned scientists and information research leaders from the Dow Chemical Company as they discuss how they built a semantic data hub with the Progress Data Platform to capture years of R&D knowledge, facilitate its discovery across the organization and make it future-ready for years to come.

During this session, we explore:

• Challenges and complexities unique to R&D data management
• Foundational data and information management needed to leverage AI
• Use of semantic knowledge graphs to contextualize and standardize R&D data 
• Integration of generative AI with Graph RAG for increased security, accuracy and accessibility

To learn how to prepare your R&D data for the future and empower your research teams to leverage LLMs and data for faster information discovery, watch now.

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