CoLab Joins NVIDIA Inception to Speed AI-Driven Engineering for Physical Products
17-Dec-2025 - ST. JOHN'S, Newfoundland
CoLab has joined the NVIDIA Inception program, NVIDIA's global ecosystem for AI innovators. The goal: help product teams move faster from concept to validation by bringing stronger AI into the workflows behind complex physical products.
Why this matters for product development
- Shorter design loops: connect modeling, simulation, and digital twins to faster decisions, so months turn into days-or hours.
- Better calls with context: capture design intent, rationale, and trade-offs so AI suggestions fit how your team actually works.
- Less rework: get the right data to the right engineer at the right time, before anything hits a test stand or the field.
Physical products aren't easy to iterate once they're built. That's why teams lean on advanced modeling, simulation, and digital twins to predict performance before committing to hardware-creating huge volumes of data that still require human judgment.
"This is about accelerating the development of products that matter," said Adam Keating, Co-Founder and CEO of CoLab. "Whether it's national security, healthcare, or the energy transition, progress in these areas depends on how quickly engineering teams can design, test, and refine complex physical systems. At CoLab, we envision a future where they can do those things much faster."
How CoLab + NVIDIA could work
NVIDIA's platforms support advanced simulation, training environments, and synthetic data generation for physical systems. CoLab can route those outputs into a structured decision flow-so critical insights don't get buried in reports or lost in email threads.
As a member of the program, CoLab will explore how to combine NVIDIA capabilities with its human-in-the-loop interface. The focus is practical: tighter loops, clearer trade-offs, and consistent decision records from concept through release.
Learn more about NVIDIA Inception
The real bottleneck: decision-making
"AI will accelerate how designs are generated and validated," said Jeremy Andrews, Co-Founder and CTO of CoLab. "But the limiting factor will be decision-making. Our focus is on capturing design intent - the discussions, rationale, and trade-offs behind engineering decisions - and using that context to make AI outputs more relevant and consistent with how teams actually work."
CoLab's vision is an Engineering Operating System for the AI era: a place where engineers review options, weigh constraints, and make calls with AI support-without removing the experts from the loop. With features like AutoReview, those decisions become repeatable patterns the system can apply across programs.
Training better AI with real engineering context
CoLab's digital design reviews create a living record of why decisions were made, not just what changed. Paired with NVIDIA-backed simulation and training environments, that context can improve the performance and consistency of engineering agents over time.
What you can do now
- Map your simulation-to-decision flow. Identify where insights stall or go unseen.
- Standardize decision records: assumptions, trade-offs, and acceptance criteria.
- Pilot a contained program with clear metrics: iteration time, ECO count, and test escape rate.
- Plan for data governance across CAD, PLM, requirements, and simulation outputs.
About CoLab
CoLab builds AI-driven software for mechanical engineering and product development teams. Its EngineeringOS connects people, data, and AI in one collaborative workspace-capturing expert knowledge as part of everyday work. With AI agents built in, CoLab helps teams improve design quality and move faster from iteration to approval.
About the NVIDIA Inception program
NVIDIA Inception is a global program that supports startups building innovative AI solutions with access to technology, expertise, and a collaborative ecosystem.
If you're upskilling your team on practical AI workflows for product development, explore focused course paths here: AI courses by job function.
"Joining the NVIDIA Inception program reflects our broader strategy," said Taylor Young, Chief Strategy Officer at CoLab. "We're building partnerships across the engineering AI landscape so our customers can take advantage of best-in-class capabilities, while CoLab provides the collaboration layer that turns those capabilities into faster, better decisions."
Founded in 2017, CoLab works with global manufacturers across automotive, industrial, energy, and medical sectors. This move signals a deeper push to help engineering teams make smarter decisions, faster.
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