A product design business was under increasing pressure to create complicated designs in shorter periods of time. Their teams spent hours on manual activities, which hampered projects and resulted in burnout. Design approvals required many days since each model had to be thoroughly evaluated by top specialists.
When they contacted us, we presented a one-of-a-kind Gen AI solution tailored to their Autodesk Maya environment. This brilliant invention utilized their greatest ideas to automate time-consuming procedures. It also spotted flaws in 3D models immediately, rather than weeks later, when repairs are more difficult. This allowed designers to concentrate more on the creative aspects of their jobs rather than the boring tasks.
Manufacturing & Product Design
AI-Enabled 3D Design Automation
We followed a clear, step-by-step approach to create a solution that truly fits the client’s needs. Each stage built on the previous one to create a system that works in the real world.
We began with deep dive seminars to learn about the client’s 3D modeling workflow, pain spots, and quality standards. Our team mapped current processes, identified automation potential, and collected samples of successful and problematic designs to train our AI.
We built a dataset using the client’s past design files. Then, we developed a custom AI algorithm to spot design trends and quality issues. The system was trained to understand top design ideas in their industry. We fine-tuned the model over multiple rounds, using feedback from the design team.
Before full deployment, we ran extensive tests on past designs. The design team carried out user acceptance testing. We measured performance by time and quality. Real-world feedback helped us refine the method further.
Before full deployment, we ran extensive tests on past designs. The design team carried out user acceptance testing. We measured performance by time and quality. Real-world feedback helped us refine the method further.
The client's design team spent lengthy hours on fundamental modeling tasks and quality checks, producing bottlenecks in the product development pipeline. Manual procedures led to inconsistent quality and extensive review cycles. Their present approaches were unable to detect structural flaws in 3D models early on, resulting in problems that were discovered later in the process when modifications were expensive and time-consuming.
The customer provided a few instances of specific edge situations required for full model training. We overcome this by creating synthetic training data and using transfer learning techniques from related fields.
Early versions of the integration hampered Maya’s performance. We redesigned our processing method, transferring heavy computing to background threads and streamlining data exchange across systems.
The impact of our Gen AI solution goes beyond simply making work simpler; it revolutionized the entire design process with tangible advantages.
Modeling time for standard components dropped by 37%. Quality reviews went from three days to just four hours. We also automated 65% of routine modeling tasks.
We detected 89% of structural flaws early, before the review stage. Revision requests from engineering reduced by 43%. Client adjustment requests delay in development fell by 28%.
The design team’s capacity increased by 30% without any extra hires. It reduced the total product development cycle by 5 weeks. And the client satisfaction rate increased by 22% with faster delivery and fewer modifications.
We converted the client’s design process into a more efficient, quality-focused workflow that allows designers to focus on innovation rather than repetition by strategically utilizing AI to augment, not replace, human creativity.
