In this webinar, we’ll show how engineering teams can move beyond isolated AI experiments and bring Agentic Engineering, AI Physics, and Compute Economics into real product development workflows.

The session will explore how a unified digital engineering platform connects simulation, data, AI, and HPC so teams can automate repetitive work, operationalise simulation-driven AI, and make smarter tradeoffs across speed, throughput, and cost.

Attendees will learn how simulation-native agents can automate tasks such as input validation, troubleshooting, diagnostics, and reporting, how AI Physics can turn historical simulation data into AI-ready datasets, surrogate models, and inference inside the tools engineers already use, and how Compute Economics helps engineering and IT leaders improve performance while maintaining visibility and control over infrastructure spend.

The benefit for attendees is a clearer, more practical view of how to apply AI in engineering today not as another disconnected tool, but as part of a scalable, production-ready workflow that helps teams reduce manual effort, expand design exploration, standardize best practices, and accelerate product development.

Attendees will learn:
● How a unified platform connects simulation, data, AI, and HPC for AI-first product development
● See how Agentic Engineering can automate diagnostics, input validation, troubleshooting, and reporting across connected workflows
● Explore how AI Physics provides a practical path from simulation data to AI-ready datasets, surrogate models, and inference in the tools engineers already use
● Understand how Compute Economics helps engineering and IT leaders improve throughput, control cost, and maintain visibility into infrastructure usage at scale
● Hear how these capabilities support engineering leaders, product development and AI teams, and CAE / methods leaders with different but connected priorities