Solutions
AI-Enhanced Customer Experiences with Relational Knowledge Graphs
A Fortune 50 retailer drove $1 billion in incremental revenues over the last three years after deploying AI models developed by RelationalAl.
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Metadata Management Series: Compliance Reasoning with Knowledge Graphs
Demonstrating the details of weaving metadata into a knowledge graph to automate checking and maintenance of complex policy requirements.
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Metadata Management Series: Weaving Asserted and Discovered Metadata into Your Data Fabric RelationalData Fabric
Showing how knowledge graphs support the construction of scalable models that mix discoverable with explicitly asserted metadata to afford reasoning and policy enforcement. In this first article, we show how explicitly asserted metadata in a knowledge graph enables automated reasoning.
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Losing the Middle Tier
Business applications are traditionally complicated to understand and maintain because business logic tends to be scattered in separate tiers of growing code bases, while schema becomes rigid and brittle. The end result is that business logic dissolves in a soup of disparate application code.
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Accelerating AI Adoption with Explainability in SaMD
Many recognize the potential of artificial intelligence (AI) in healthcare and life sciences. Some early adopters are starting to reap the benefits already, especially in fields such as radiology and digital pathology.
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RAI Platform Workload Scenarios
The RAI relational KGMS combines Graph, Reasoning, and Learning in a single platform. Add cloud scalability, workload concurrency, and zero-copy cloning to get unique analytic flexibility.
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