Latest News in CAD and AI
Here are some of the latest significant developments at the intersection of CAD, CAE, PLM, digital engineering, and AI.
ClassCAD.ai — AI-Driven CAD Through MCP
ClassCAD.ai has launched an embeddable, AI-driven CAD system with its own MCP server. Users can describe a part in natural language and an AI agent can create and verify the model. It supports parametric modeling, constrained sketches, NURBS geometry, and STEP output, and can connect with AI systems including Claude, Codex, and others.
Adam — AI-Powered Parametric CAD Migration
Adam launched Migrations, using AI agents to rebuild a CAD model’s native parametric feature history inside another CAD system rather than simply translating geometry.
The system reconstructs features step-by-step, verifies the rebuilt geometry against the original, and can transfer metadata. Supported migration targets include SOLIDWORKS, Onshape, Autodesk Fusion, Siemens NX, CATIA, Inventor, and Creo.
Autodesk — Agentic CAD, Manufacturing and PLM
Autodesk has expanded Autodesk Assistant across Fusion, Inventor, Vault, and other Design and Manufacturing products.
Fusion now has separate MCP capabilities for live CAD execution, engineering-data access, and cloud-based design/manufacturing workflows. Autodesk has also previewed agentic PLM in Fusion Manage, where AI can analyze product and workflow context, predict impacts, coordinate work, and recommend next actions.
Siemens — AI in Teamcenter PLM
Siemens is expanding AI within Teamcenter around the actual context of product structures, requirements, configurations, BOMs, engineering changes, manufacturing processes, and quality information.
The direction goes beyond searching PLM documents toward AI that understands product relationships and can support impact analysis and engineering-change/BOM workflows.
https://blogs.sw.siemens.com/teamcenter/ai-in-plm-teamcenter
Simio — MCP for AI-Driven Simulation and Manufacturing Planning
Aegis Software added built-in Model Context Protocol support to Simio, allowing compatible AI systems to interact directly with discrete-event simulation and advanced planning and scheduling.
Using natural language, users can generate and refine simulation logic, troubleshoot models, run and analyze experiments, and investigate production plans.
Quanscient — Agentic Multiphysics Simulation
Quanscient’s Allsolve Agent brings agentic AI and natural-language interaction directly into multiphysics simulation.
Users can describe simulation tasks in plain language while the agent builds or modifies models and works within the simulation environment. The Allsolve Agent is currently in beta and available to all Allsolve users.
Siemens + TSMC — Agentic AI for Semiconductor Design
Siemens and TSMC introduced an AI-powered workflow that can identify, analyze, and resolve design-rule-check violations using Siemens Calibre integrated with Aprisa and Solido.
The broader Fuse EDA AI Agent is designed for multi-step engineering workflows across EDA tools, moving agentic AI deeper into semiconductor design and verification.
Jacobs + NVIDIA — AI Agents and Omniverse Digital Twins
Jacobs is deploying an NVIDIA Omniverse-based Data Center Digital Twin at a large NVIDIA R&D facility.
The platform combines engineering models, operational technology, simulation, and live facility data. Jacobs says it is evolving the digital twin toward an intelligent operating system where AI agents can predict conditions, recommend actions, and increasingly optimize operations autonomously.
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