Unlock the full capabilities of your organization
THE ARCHITECTURE
User-Centric Technology
At EighthPARALLEL, we turn enterprise data into a strategic advantage. Our Semantic Field™ Technology seamlessly connects modern and legacy systems, ensuring they can share information securely across diverse systems with minimal human intervention.By structuring and enriching data, we help businesses streamline operations while providing the clarity, control, and confidence needed to maximize the value of their data and AI investments.
ONTOLOGIES
Ontologies are formal representations of knowledge that define concepts and the relationships between them within a domain. They focus on defining the semantics of terms and how they relate to each other for clear knowledge representation and reasoning.
Ontologies are used to define the structure or flexible schema of a knowledge graph by providing a formal description of the concepts and relationships that the knowledge graph will represent.
KNOWLEDGE GRAPHS
Knowledge Graphs are a flexible way to represent complex networks of interconnected information. They incorporate ontologies by aligning their structure with the concepts defined in the ontology.
While ontologies provide a formal way to define concepts and relationships within a domain, knowledge graphs provide a practical way to represent and utilize knowledge in various applications. Together they enable reasoning and inferencing to uncover implicit knowledge.
THE PLATFORM
Semantic Enterprise Solutions
We are firm believers in open architecture. We configure software that interoperates with our clients' existing tools and enables them to innovate quickly by adopting new technologies as they become available. The approach reduces vendor lock-in, increases flexibility, and promotes enterprise-wide interoperability regardless of existing applications.
KNOWLEDGE GRAPH DATA STORE
Our solutions can act as an analytical layer and/or a system of operation. Unlike other Knowledge Graph platforms, our solution can be a read/write database that can connect to systems and consumers via simple HTTP, API, or 2-layer application architectures.
HYPER-PERSONAL DATA ACCESS
Our platform unlocks an unprecedented level of employee and customer personalization opportunities around data. This innovative neural network maps intricate relationships, empowering organizations to offer their users experiences specifically tailored to their needs.
ZERO TRUST SECURITY
Our technology can embed fine-grained access policies into your Knowledge Graph database, making it easier and more accessible to share only the right data with the right consumers. Dynamically leverage relationships within the graph to determine identity and access.
KG vs RDBMS
Knowledge graphs (KG) embrace the semantic aspect of data, allowing for the expression of complex relationships and semantics through ontologies. Relational databases (RDBMS) excel at managing structured data and supporting transactions, but enforce rigid schemas, requiring predefined structures and types for data storage.
While relational databases primarily focus on data storage and retrieval, knowledge graphs provide a unified framework for integrating heterogeneous data types and formats, enabling a holistic view of information across domains and systems. They support flexible and context-aware querying, empowering users to explore complex relationships and derive insights from interconnected data.
SEMANTIC LAYER vs DIGITAL TWIN
A semantic layer is an abstraction layer that translates complex data into business-friendly terms. It provides a representation of data across different systems and databases. A digital twin is a virtual representation of a physical object, process, or system. It replicates the behavior, characteristics, and functionalities of its physical counterpart in a digital environment.
While both concepts involve abstraction and representation, a semantic layer simplifies data access, enabling users to query and analyze data without needing to understand its underlying complexities. Whereas a digital twin typically only focuses on creating virtual replicas of physical entities for simulation and analysis.
