CoLab has introduced a new AI-driven solution designed to mitigate risks, improve quality, and safeguard technical knowledge within the realm of mechanical product design.
This is the first solution of its kind to leverage AI and machine learning applied to a natural language dataset, enabling a systematic approach to gathering human feedback for enhanced product design processes.
A survey conducted among 250 engineering leaders at large-scale companies highlighted that 43% of product design review data is lost, and 87% of these leaders face significant delays, spending hours or even days to find the necessary information for a single design decision.
CoLab collaborates with several prominent engineering companies, including Ford Pro, Johnson Controls, and Mainspring Energy, to accelerate design cycles, prompt earlier revenue realization, reduce bill of materials costs, and achieve substantial cost-saving targets.
According to Adam Keating, Co-Founder and CEO of CoLab, "Most product design teams still have to rely on manual processes for design reviews. This means technical feedback is shared in meetings and documented inconsistently with admin-intensive tools. The result is slow and ineffective decision-making and an ever present risk that when key subject matter experts leave the company or retire, their expertise will go with them."
CoLab's core Design Engagement System (DES) supports asynchronous reviews of 2D and 3D models, automatically generating a comprehensive database of technical comments as engineers go about their routine tasks.
The newly launched application utilizes machine learning to draw parallels between similar design issues, linking historical feedback and insights to inform current design decisions. This mechanism helps prevent recurring design errors and allows engineers to dedicate more effort to complex problems and innovation.
Adam Keating further explains, "In today's competitive market, there is no room for overspend, product delays or expensive recalls, which have a big impact on market reputation and customer loyalty, and could take a company back years."
CoLab is actively working on advancements that will incorporate valuable downstream data into the design reviews while also developing auto-review capabilities for basic design verifications, aligned with user-defined checklists.
As generative AI continues to evolve, CoLab maintains strict adherence to security policies to protect intellectual property. The company assures its clients that it does not utilise sharing across customer data for model development, thus ensuring a trusted solution for Fortune 500 manufacturers.
