How Do You Maintain Consistency When Using Multiple AI Image Models for Product Shots?

I’m running into a recurring issue when creating product visuals. One model handles materials and lighting well, another is better at fixing hands or labels, and a third produces stronger stylistic results. Switching between tools usually causes the object to drift, so the final files no longer match.

How are other developers and teams handling this?

I’ve been testing AI Image as a possible approach. It brings Flux, Midjourney, GPT Image, and other models into a single interface with a shared credit balance. You can generate from a prompt or reference photo, compare the same brief across engines, then edit specific problems on the existing image instead of regenerating from scratch. Restyling keeps the same parent subject for different crops or moods. The free tier covers the full generate → edit → restyle loop; paid plans add speed, resolution, batch processing, and a commercial license with no watermark. No local GPU is required.

Is a unified multi-model workflow the practical solution here, or are most people still regenerating independently and accepting the inconsistency for product pages and marketing assets? Curious what approaches are working in practice.