Shoperator.ai owns the creative product and brand. Ego Eimi’s delivery, with Abhishek Gawade, covered the AI generation layer and infrastructure that turn Shopify product information into reviewable advertising creative.
A merchant already has product information, images and a brand identity. Turning those inputs into fresh advertising creative repeatedly requires a process for carrying that context into each output.
The product needed more than an image-generation endpoint. Store connection, brand context, editing, execution and the team’s administration tools all had to work together.
The Shopify integration supplied catalog information to a brand-book and generation workflow. The pipeline produced product imagery and advertising layouts, with editing variations through the Magic Edit feature.
The work included the supporting infrastructure, integrations and administration tools. Next.js and TypeScript formed the application layer, with Python, diffusion models, LLMs, PostgreSQL and AWS in the generation and operating stack.
AI generation and product infrastructure. The delivery section explains the workflow demonstrated here.
The delivered system connected merchant inputs to creative generation inside Shoperator.ai’s product. Application behavior and the generation infrastructure formed one operating scope, supporting changes to the product and its underlying models.
An AI product’s operating costs and behavior depend on the generation pipeline. Its owner needs visibility into failed jobs, provider changes, brand inputs and output review. Tech Team is built around owning an agreed technology scope of this kind while the business retains its product and accounts.
Project contribution: Abhishek Gawade. The scope described above identifies the work behind this case.
Editorial review: Ego Eimi · Updated September 6, 2026 · About the team
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