AI-native simulation and modeling company JuliaHub reports a strategic partnership with Synopsys to integrate Dyad, JuliaHub’s flagship next-generation simulation platform, into Ansys TwinAI artificial intelligence-powered digital twin software, part of the Synopsys portfolio.
This collaboration brings together JuliaHub’s expertise in AI-driven, physics-informed simulation with Synopsys digital twin technology.
TwinAI enables organizations to validate and operate digital twins in cloud environments that support advanced simulation engines, operating systems, and data streams. The platform offers capabilities to simulate digital twins, enhance model accuracy using Hybrid Analytics, and simplify cloud deployment, according to Ansys.
With the integration of Dyad, TwinAI will combine physics-based simulation with adaptive AI models, enabling engineers to create “hybrid digital twins” that are predictive and grounded in physical laws.
“A digital twin is more than a model. It’s a living, dynamic representation of a system,” says Dr. Prith Banerjee, senior Vice president at Synopsys. “By integrating Dyad and JuliaHub’s SciML technology, TwinAI empowers engineers to build digital twins that evolve with data, bridging the gap between simulation and reality.
Dyad’s component-based, acausal modeling and automatic equation generation enable capacity to design and extend complex, multi-domain systems. Paired with Ansys simulation capabilities, the integration brings new capabilitiesfor real-time simulation, predictive analytics, and scalable cloud-based digital twin deployment.
“This partnership brings JuliaHub’s scientific machine learning innovation to one of the world’s most trusted simulation ecosystems,” says Viral B. Shah, CEO and co-founder of JuliaHub. “Together, we’re enabling the next generation of intelligent digital twins which is adaptive, explainable, and deeply rooted in physics.”
Dyad brings cloud-native infrastructure, differentiable programming, and modular extensibility to support engineering workflows. Dyad enables the development of digital models by integrating AI with Scientific Machine Learning (SciML) in an engineer-in-the-loop, environment.
Sources: Press materials received from the company and additional information gleaned from the company’s website.

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