Connected Intelligence for Strategic Advantage
As organizations gather extensive volumes of diverse data across business lines, the opportunity to extract unified understanding grows exponentially. However, information residing in application silos or disconnected systems limits strategic perspective. An enterprise knowledge graph (EKG) addresses this challenge by establishing a virtual intelligence nucleus linking relevant entities and semantics from distributed sources.
AI algorithms identify and connect related entities like customers, products or assets referenced across diverse sources.
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Relationship Extraction
Semantic annotations reveal how extracted entities interact based on text, behavioral and event data analysis.
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Data Discovery
Search and browse graph embeddings to find connected information popular for analytics and system integration needs.
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Process Automation
Predefined event-based rules trigger actions when graph relationships meet specific conditions.
Intelligent Search
Our intelligent search solutions apply machine learning to index vast semi-structured repositories and surface the most useful information to answer queries.
By customizing models to your unique content domains, we help organizations harness insights from visual assets to optimize operations, enhance experiences and more.
Our recommender solutions apply machine learning to analyze user behavior and item attributes, delivering individualized suggestions that drive engagement and satisfaction.
Our knowledge graph solutions build contextual taxonomies linking entities across your data ecosystem to power predictive analytics, personalization and more.
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Go to Use Case Title
What Are the Advantages You Should Expect?
Context Awareness
Deeper insights emerge from exploring how different business facets interrelate beyond isolated viewpoints.
Knowledge Reuse
Common domains and taxonomies established in the EKG facilitate sharing understandings across divisions.
Data Virtualization
Applications and users leverage a virtual abstraction of truth computed dynamically from distributed sources.
Process Optimization
Automated decision-making based on relationship inferences improves consistency, compliance and resource allocation.