Vention Opens Physical AI And Robotics Lab In Montreal
The lab's research agenda combines industrial data collection, robotics control, motion planning, classical computer vision, vision foundation models, learning from demonstration, and reinforcement learning, aimed at manufacturing tasks that are complex and unstructured.
The lab has already generated new intellectual property and will continue to as this work advances.
The mandate is scalable deployment: validating new physical AI capabilities against the reliability, cost, and variability requirements of real production lines.
As the underlying models mature, Vention expects the complexity costs of deploying to drop, widening the range of manufacturers who can put physical AI to work on their floors.
Canada's 'leading physical AI lab for manufacturing'With technology deployed across thousands of manufacturers globally, including 90 of the Fortune 500, Vention's scale gives researchers direct access to real manufacturing environments and a continuous stream of industrial manipulation data to post-train Physical AI models.
Physical AI is Vention's fastest-growing segment, with related revenue up 400 percent over the past year. That combination of academic research and a live industrial base sets the lab apart from other industry players. Model development is shaped by benchmarks, but also by client feedback, production challenges, and day-to-day deployment conversations.
Etienne Lacroix, founder and CEO of Vention, says:“Physical AI will fundamentally expand what manufacturers can automate, but the challenge is no longer simply proving that a robot can perform a task in a lab.
“The real opportunity is making these capabilities reliable, economical, and deployable across thousands of factories. By combining Canada's world-class AI ecosystem with Vention's deep robotics expertise, industrial data, and full-stack automation platform, we have a unique foundation to close that gap.”
Dr Jimmy Li, director of physical AI, says:“What makes this lab different is the loop we've built: academic research feeding directly into live production problems, and production feedback feeding back into the research.
“Our clients aren't waiting for a finished product to test; they're in the room while we build it. That's unique in this field, and it's what lets us move faster from a research result to something that actually runs on a factory floor.”
From AI research to industrial deploymentVention's physical AI lab is led by Dr Jimmy Li, a robotics and machine learning researcher from McGill University who brings more than a decade of peer-reviewed research experience and deep expertise in computer vision, robot perception, autonomous systems, and AI-powered robotic manipulation.
Over the past two years, he has spearheaded Vention's physical AI strategy and led its technical collaboration with Nvidia, translating advances in AI research into commercial robotic applications deployed on factory floors.
A key innovation from the physical AI lab is GRIIP, launched in February 2026. It is a modular physical AI pipeline that spans scene digitalization, object segmentation, pose estimation, grasp selection, and collision-free motion planning, leveraging foundation models from technology leaders including Nvidia as well as Vention's proprietary models.
As a continuation of the development process, Vention will release a public GRIIP Software Development Kit (SDK) enabling engineering teams to further develop the pipeline to fit their unique needs.
Vention is also working with global industrial and electronics manufacturers, including a large automotive OEM on high-complexity, unstructured robotic tasks in final assembly.
Bringing world-class AI expertise to industrial roboticsDr Pineau joins Dr Li in an advisory capacity as external technical advisor. Her contributions will span model architecture decisions, research prioritization, and connections into the broader AI community as the lab expands its work at the intersection of foundation models, robotics, and industrial automation.
Legal Disclaimer:
MENAFN provides the
information “as is” without warranty of any kind. We do not accept any
responsibility or liability for the accuracy, content, images, videos,
licenses, completeness, legality, or reliability of the information
contained in this article. If you have any complaints or copyright issues
related to this article, kindly contact the provider above.

Comments
No comment