PTC Launches Onshape Labs to Test AI Capabilities Within Product Development Workflows

July 20, 2026

ByMarianne D’Aquila

Category:

Company and Product News

The early-access program will allow Onshape users to evaluate AI-assisted rendering, drawing validation, engineering automation, code generation, and robotics simulation capabilities directly within the cloud-native CAD and PDM environment.

PTC has introduced Onshape Labs, an early-access program that will provide customers with access to emerging artificial intelligence and automation capabilities within its Onshape cloud-native computer-aided design (CAD) and product data management (PDM) platform.

The program is intended to allow participating customers to evaluate capabilities earlier in the development cycle and provide feedback before their potential broader release. PTC expects to make Onshape Labs more widely available later this summer through an opt-in setting within Onshape Preferences.

Onshape Labs reflects PTC’s effort to incorporate AI directly into engineering and product development workflows rather than offering it through separate applications. Because Onshape records design changes and product data within a cloud-native environment, PTC plans to use this information to provide AI systems with the context needed to interpret design intent, automate tasks, and assist with engineering decisions.

Initial Onshape Labs Capabilities

The initial capabilities available through the early-access program include:

AI Quick Render: Uses text prompts to generate product renderings from Onshape designs.
Onshape-to-NVIDIA Isaac Sim Workflows: Transfers CAD assets from Onshape into NVIDIA Isaac Sim, with NVIDIA Omniverse libraries supporting simulation-ready visualization for robotics development teams.

PTC previously introduced a connected workflow between Onshape and NVIDIA Isaac Sim to help robotics teams transfer mechanical designs into simulation while preserving joints, actuators, and other physical relationships. The workflow is designed to reduce the manual work involved in recreating this information after exporting CAD models.

AI Agents, Drawing Validation, and Prompt-Based CAD

PTC also outlined several capabilities expected to become available through Onshape Labs:

AI Agents and Automation: Agents designed to perform engineering tasks, apply standards, and work alongside users while retaining human oversight.
Drawing Checker: An AI-assisted validation capability intended to determine whether engineering drawings conform to defined standards.
FeatureScript Model Context Protocol Server: A text-to-code-to-CAD framework that will allow users to generate CAD geometry and customize Onshape through natural-language prompts.

The proposed agent capabilities could move AI use within CAD beyond content generation and recommendations toward the execution of defined engineering tasks. Maintaining visibility into agent actions and allowing engineers to review or override results will be important as these tools begin affecting product definitions and engineering documentation.

The FeatureScript capability could also make CAD customization more accessible by translating natural-language instructions into code and geometry. However, generated results will still require engineering review to ensure that designs meet functional, manufacturing, safety, and regulatory requirements.

Using Product Data to Provide Engineering Context

One of the challenges associated with applying AI to engineering is providing models with sufficient product context. Generic AI systems may be able to generate text, images, or code but typically lack access to the design history, engineering relationships, versions, approvals, and product structures needed to make informed product development decisions.

Onshape combines CAD and PDM capabilities within the same cloud environment and maintains a continuous history of product changes. PTC intends to use this product data foundation to help AI capabilities understand previous design decisions and operate within the context of active engineering work.

This approach supports PTC’s broader Intelligent Product Lifecycle strategy, which focuses on creating a consistent product data foundation and extending that information across engineering, manufacturing, service, and other enterprise functions.

The value of these capabilities will depend on whether AI-generated recommendations and actions can be traced to the relevant product information. Engineering teams will need to understand what data an AI system used, what changes it made, and whether those changes comply with internal standards and product requirements.

Early Access Supports Customer-Led Development

Onshape Labs will allow PTC to expose emerging capabilities to users before deciding whether to incorporate them into the standard Onshape product. Customer feedback could help the company identify useful engineering applications, usability problems, and areas where additional controls are needed.

PTC has noted that Labs capabilities may be modified, withdrawn, or released more broadly depending on the results of the early-access program. This model allows the company to test AI functionality in practical engineering environments without presenting every experimental capability as a completed product feature.

The program also provides participating customers with an opportunity to assess how AI could affect existing design processes, engineering roles, product data governance, and approval workflows before adopting the technologies more broadly.

Related ARC Insights

Additional ARC Advisory Group coverage provides context on the technologies supporting the Onshape Labs initiative:

Onshape Labs illustrates how AI is beginning to move into the systems where engineering data is created and managed. Its broader effect will depend on whether PTC can demonstrate that these capabilities improve engineering productivity and design quality while preserving the traceability, control, and accuracy required throughout the product development process.