Neural Concept Unveils AI Design Copilot at CES 2026
Last week at CES 2026, Neural Concept introduced its AI Design Copilot, a significant advancement for engineering workflows aimed at enhancing design and simulation processes. This feature, part of their AI-driven product development platform, follows a notable $100 million funding round. The AI Design Copilot focuses on improving geometry generation. By utilizing text prompts, engineers can create various design iterations that can then be simulated using established platforms such as STAR-CCM+, the Ansys suite, and OpenFOAM. The results from these simulations can flow back to Neural Concept for further analysis, optimizing designs based on real performance data.
This functionality addresses a common bottleneck in engineering: the lengthy process of generating design data and variants. With successful trials indicating “overwhelmingly positive” feedback, users can anticipate significant reductions in time spent on design exploration. In addition, Siemens unveiled its Digital Twin Composer, which integrates digital twin models with real-time data sources, including IIoT sensors and quality management systems. As part of Siemens’ Xcelerator portfolio, this application aims to connect 2D and 3D models, bringing a new level of accuracy to the simulation of industrial environments. Initially used by PepsiCo to model its manufacturing and warehouse facilities, the tool promises to enhance compliance and operational efficiency by creating dynamic, photorealistic visualizations.
Bentley Systems expanded its asset analytics capabilities through the acquisition of Talon Aerolytics and the intellectual property of Pointivo. These additions aim to enhance infrastructure lifecycle management, particularly in the operation and maintenance sector, where there is a growing need for efficient asset management. Overall, these developments present significant opportunities for engineering teams focused on process efficiency, accuracy, and scalability in their workflows. The integration of AI and real-time data into design and operational processes marks a progressive shift towards more automated and data-driven engineering practices.
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