Leading Companies Leverage Graph-Powered Digital Twins to Manage Interconnected Complex Systems

Neo4j, one of the world’s leading graph data platforms, has announced a sharp increase in demand for graph technology for digital twins. Graph technology is being used by organizations to create large-scale digital twins capable of combining data from different sources, giving sophisticated analytics, and allowing near real-time monitoring of important assets.

The digital twin market was estimated at $6.9 billion in 2022 and is expected to grow to $73.5 billion by 2027. Furthermore, Gartner projects that 25 worldwide organizations would achieve $1 billion in revenue or cost savings from digital twin activities by 2025, up from one in 2021. Source: Gartner, Emerging Technologies: Revenue Opportunity Projection of Digital Twins, Alfonso Velosa et al.,16 Feb 2022. While the benefits of digital twins are obvious, the amount of effort required to develop them might be overwhelming. An effective digital twin is built using huge amounts of diverse data from various sources and formats, including 3D models, accounting systems, operational systems, and data from IoT devices.

A knowledge graph excels in integrating complicated data and modeling enormous real-world structures and business logic in a flexible manner. Organizations can manifest a digital twin in any structure or process within any industry using Neo4j’s graph database as the foundation, resulting to a wide range of use cases. The graph data platform from Neo4j delivers the flexibility, performance, and analytical capabilities required to affordably develop, maintain, and query digital twins on an enterprise scale, combining data from disparate sources to provide the maximum business value. Graphs provide advanced analytics and powerful queries in digital twins, as well as data science and machine learning techniques ranging from algorithms to embeddings.

Neo4j Digital Twin Customer Success

Customers employ Neo4j graph technology to assist in the development of cutting-edge digital twins across a wide range of sectors and use cases. Supply chain digital twins provide visibility into complex networks, integrate varied product validation life cycle data for automotive, and replicate complex manufacturing lines in life sciences manufacturing.

Agility is well positioned for organizations that have used Neo4j graph technology as part of their digital twin project. Here are some examples of how they use Neo4j to move crucial initiatives forward:

According to Dave Rich, Head of Enterprise Architecture and IT Services at CSX Transportation, a significant provider of rail-based freight transportation in North America, Neo4j was selected to assist them in creating a digital twin model of their physical network.

Turku City Data uses a ‘Smart City Knowledge Graph’ to support its digital twin to address key city priorities such as reducing energy usage and finding routes that optimize delivery speed and transportation resources.

Neanex provides Neo4j-based digital twin services that enable asset owners to establish a digital twin that integrates all types of data, from 3D models to building permits.

A significant worldwide F100 pharmaceutical company has built a Neo4j-powered digital twin to support a wide range of supply chain use cases, including simulations for decision-making, cost and time optimizations, risk assessment and mitigation, and manufacturing line design alternatives.

Organizations obtain a distinct competitive advantage by combining the power of graph technology and digital twins. As the world’s digital landscape evolves, these virtual counterparts will become increasingly vital in inventing previously inconceivable optimal solutions.