Tag: Progress Data Platform

For life sciences R&D teams, many of the obstacles to useful data and AI extend beyond one company’s systems. Research information moves among laboratories, partners and disciplines, yet the meaning of a term, the source of a finding or the rules for using a dataset may not move with it. Read about Progress' membership with the Pistoia Alliance and its approach to connected data, semantic context and governance for enterprise AI and analytics.

When it comes to FAIR life sciences data, keeping meaning and detail attached to pharmaceutical data supports trusted reuse across R&D, technology transfer and CDMO operations. Semantic harmonization can preserve source detail, add semantic context and relate different worlds without flattening them. Progress Data Platform helps connect complex data, documents and domain knowledge so information remains findable, reusable and trustworthy across teams, systems and partners.

At the Progress Data Platform Summit, Progress Software Fellow Ramon Navarro Bosch argued that a confident AI answer is not a trustworthy one. His blueprint combines LLMs with an enterprise semantic layer of ontologies, taxonomies and a validated knowledge graph, so every fact behind an answer can be traced, checked and reproduced

Discover how Progress Data Platform connects fragmented manufacturing data to support smarter decisions, stronger traceability and AI grounded in business context.

Membership in the International Press Telecommunications Council, or IPTC, allows organizations to better understand how metadata, semantic context and governance can support trustworthy content discovery and responsible AI. Whether you're modernizing content archives, improving discoverability, enriching metadata or building trusted AI workflows for publishing, Progress Data Platform can help connect content, context and governance at scale.