Entity-Event Knowledge Graph Solutions: Franz Inc.
Ubiquitous AI requires a new data model approach that unifies typical enterprise data with knowledge bases such as taxonomies, ontologies, industry terms and other domain knowledge.
Franz’s Knowledge Graph approach encapsulates a novel Entity-Event Model, natively integrated with domain ontologies and metadata, and dynamic ways of setting the analytics focus on all entities in the system (patient, person, devices, transactions, events, operations, etc.) as prime objects that can be the focus of an analytic (AI, ML, DL) process.
The Entity-Event Data Model utilized by AllegroGraph with FedShard puts core “entities” such as customers, patients, students or people of interest at the center and then collects several layers of knowledge related to the entity as “events.” Events represent activities that transpire in a temporal context.
The rich functional and contextual integration of multi-modal, predictive modeling and artificial intelligence is what distinguishes AllegroGraph as a modern, scalable, enterprise analytic platform. AllegroGraph is the first big temporal Knowledge Graph technology that encapsulates a novel entity-event model natively integrated with domain ontologies and metadata, and dynamic ways of setting the analytics lens on all entities in the system.
Financial institutions, healthcare providers, contact centers, manufacturing firms, government agencies and other data-driven enterprises that use AllegroGraph gain a holistic, future-proofed Knowledge Graph architecture for big data predictive analytics and machine learning across complex knowledge bases in order to discover deep connections, uncover new patterns and attain explainable results.
Contact Franz Inc. today to build your Knowledge Graph solution.
Franz Inc.- AllegroGraph
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