AI Product Render Pipeline

The problem

Product renders were a bottleneck. Every new concept, colorway, or material variation required a designer to manually set up a scene, light it, and render it. A single product could take a full day to visualize across all its variants. The design team was spending more time rendering than designing.

The approach

I built a pipeline that takes basic product inputs and generates photorealistic renders using generative AI models, tuned for the brand's visual language. The system was designed to fit into the existing creative workflow, not replace it.

• Generative AI models fine-tuned on the brand's existing product photography and visual identity
• Batch processing for generating multiple angles, materials, and colorways from a single input
• Output formatting that matches the team's existing asset pipeline, ready for presentations and catalogs
• Human-in-the-loop review step so designers maintain creative control over the final output

The outcome

Iteration cycles dropped from days to hours. Designers could explore more variations earlier in the process, which meant better decisions before anything went into production. The pipeline didn't replace the design team's eye, it gave them more material to be selective with.

What I learned

Creative teams are rightfully skeptical of AI tools that promise to "do their job." The key was positioning the system as a prototyping accelerator, not a replacement. Designers use it the same way they'd use a mood board: to explore directions quickly before committing to the one that works. The moment it felt like a tool they chose to use rather than one imposed on them, adoption stopped being a problem.