Read about how connecting fragmented biomedical data into a structured knowledge graph and making it queryable in plain language helps Life Sciences organizations move faster and with more confidence.
read moreArchive for "Scientific Knowledge Management"
Blog Post
When FAIR Becomes Architecture: Solving Preclinical Data Fragmentation at Scale
Read about how a top-5 global pharma company transformed a fragmented preclinical in vivo data landscape into a semantically rich knowledge graph
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Blog Post
Accelerating Discovery — How GraphRAG Drives ROI in R&D and Knowledge-Intensive Workflows
Read about how GraphRAG helps organizations cut search time, speed up discovery, and turn AI pilots into measurable ROI.
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Blog Post
AstraZeneca: Enabling New Medicines Through Semantic Knowledge Graphs
Read this abbreviated & updated version of a talk from the Graph AI Summit 2025 by Ben Gardner, AstraZeneca
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demo
Biomedical Data Discovery
Demonstrates how natural language access to complex biomedical data lets researchers ask questions directly and surface relevant relationships – cutting down manual data exploration and speeding up hypothesis generation.
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Blog Post
How Graphwise Semantic Analytics Facilitates Stroke Care
Read about how Graphwise technology enables medical experts to input data faster into the Registry of Stroke Care Quality
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Success Story
Building a Collaborative Knowledge Hub for AI-Powered Predictive Intelligence
Sensing Clues implemented Graphwise’s Knowledge Management Suite to build vast organizational knowledge models.
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Resource
Talk to Linked Life Data
Learn how Graphwise’s natural language query interface empowers scientists to explore target identification as easily as asking a question.
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demo
CABI Digital Library
Demonstrates how semantic search helps users quickly find the most relevant research across a vast library – reducing time spent sifting through publications and enabling faster access to actionable insights in agriculture and environmental challenges.
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demo
Target Discovery
Demonstrates how linking fragmented biomedical data helps researchers quickly identify potential therapeutic targets – reducing time spent integrating sources and accelerating early-stage discovery.
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