The Digital Twin Consortium® (DTC) announced the first testbeds as part of its Digital Twin Testbed Program. This collaborative member-driven program accelerates development, validation, and implementation, demonstrating digital twin evolution with agentic AI and enabling technologies. By providing unprecedented access to early-stage testbed development, members can model, simulate, integrate, rigorously verify, deploy, and optimize digital twin solutions while collectively advancing the core technologies that power tomorrow’s digital transformation.
The Digital Twin Testbed Program implements DTC’s Composability Framework—utilizing the Business Maturity Model, Platform Stack Architecture, and Capabilities Periodic Table—alongside a capabilities-focused maturity assessment framework that incorporates the evaluation of Generative AI, multi-agent systems, and other advanced technologies.
“We’re excited to announce these innovative digital twin testbeds,” said Dan Isaacs, GM & CTO of the DTC. “We’re seeing strong interest from members worldwide in participating in our collaborative testbed program. Our members are already utilizing this program to develop further and adopt intelligent and generative digital twins and other enabling technologies.”
New DTC member-led testbeds include:
- Virtual Twins for Smart Factory Innovation – In an era of intensifying competition, skills shortages, and unstable demand, the need for modernized production facilities has never been greater. The testbed highlights the importance of digital twins in virtually simulating production lines, driving innovation, reducing commissioning time, and leveraging operational data for continuous improvement. Dassault Systèmes leads this testbed.
- Cognitive Network Orchestration – This testbed validates the capability of agent-based digital twins to communicate across industrial and business domains using standardized manufacturing ontologies. It implements a digital twin-based multi-agency framework with operational infrastructure and communication protocols to create a network of intelligent agents that operate across organizational boundaries. XMPro leads this testbed with Microsoft.
- Generative AI for Healthcare Digital Twins – The testbed evaluates a GenAI agent’s ability to use retrieval-augmented generation (RAG) with graph data in healthcare. It uses Axomem’s cloud and Azure AI Foundry to assess agent accuracy, cost optimization, and safe interaction with sensitive data. Stakeholders include hospital representatives and DTC members, aiming to demonstrate secure and efficient GenAI deployment. Axomem leads this testbed.
- A Blueprint for Property and Asset Risk Management – This testbed develops a standardized digital twin blueprint for moving from paper-based processes to real-time, AI-driven asset management. Integrating Martin’s Law-aligned fault scenarios will improve efficiency, ESG outcomes, and compliance. Phased testing and A/B comparisons validate a scalable, transformative model for diverse industries. Crysp leads this testbed in partnership with NEXUS (at The University of Leeds) and TUV SUD, with support from XMPro, DNV, SLB, the Ferdinand-Steinbeis Institut, Ingenuity Leeds, and Oakridge High School.
- Automated Negotiation with Digital Twins and MAGs – This testbed validates the capability of systems to automatically negotiate agreements across organizational boundaries using digital twins for utility evaluation. It further shows how this capability can be integrated with multi-agent generative systems (MAGS) for improved interactivity, reasoning, and autonomy while maintaining institutional policies. NEC leads this testbed with XMPro.
- Digital Engineering for the Next Generation – This testbed is a digital engineering ecosystem for developing assets, accelerating skills, acquisition, and workforce development. It explores the end-to-end digital engineering experience and captures a digital thread of all associated data from design to manufacturing of a “born qualified” asset. The initial asset will be a desk-top statue of a historical figure from the Manhattan Project, including a digital twin AR avatar that can be “chatted” with. Oak Ridge High School leads the testbed with XMPro, Sev1Tech, SLB, STEM TEC Services LTD, Ingenuity Leeds, and Dassault Systèmes.
- Sustainable Energy Digital Twin for Operational Management – The testbed demonstrates a no-code enterprise platform for creating a full-featured, AI-ready digital twin for geothermal operations. It also shows scalable digital twin systems for complex energy infrastructure, enabling rapid deployment, spatial integration, predictive maintenance, and event handling in the renewable energy and industrial operations domain. Decimetrix leads this testbed.
- Digital Twins for Metal 3D Printing and Optimization – The testbed addresses the demand for high-quality production of complex geometry metal alloy parts. It demonstrates an IoT-enabled, state-of-the-art 3D metal printer coupled with a digital twin development architecture to achieve real-time, closed-loop control and diagnostics/prognostics capabilities. This integration enhances manufacturing quality and interoperability, advancing industry knowledge in digital manufacturing. Rowan University and XMPro lead this testbed.
