It includes NVIDIA tools and a framework for moving engineering AI from pilots to broader deployment.
SimScale has launched the Engineering AI Blueprint for CTOs and engineering leaders who are planning to deploy AI agents in engineering workflows. The blueprint includes NVIDIA technologies for accelerated computing and physics AI models and tools.
Moving from pilot projects to broader deployment can be difficult, especially when AI agents are used in design workflows. The blueprint draws on engineering projects and customer deployments to outline a framework for scaling engineering AI.
The blueprint notes that conventional verification and validation processes can leave key design decisions too late in the development cycle. It cites one study in which decisions made before design freeze accounted for 86% of expected program cost and late-found concept defects required about 13 times more rework. It proposes a process in which exploration comes before selection, validation starts earlier and physical testing is used for confirmation. It also defines where agent autonomy should be limited.
The blueprint outlines the software layers needed for autonomous workflows, from orchestration to a knowledge layer controlled by the organization. It also identifies where NVIDIA PhysicsNeMo, NVIDIA Nemotron and the NVIDIA NeMo Agent Toolkit fit in the stack.
A survey SimScale conducted earlier this year among 350 engineering leaders at organizations with 1,000 or more employees found that 99% expected measurable ROI from AI within 12 months. The blueprint maps how CTOs and engineering leaders can assess the results of AI deployment.
For more information, visit simscale.com.
