Fidelity
The garment stays the subject.
Image editing starts from the source photograph, preserving the color, print, texture, logo, and silhouette a shopper expects to receive.
AI apparel photographyBuilt for batches
Turn up to 100 apparel images into ecommerce-ready photographs of real-looking models—without planning a shoot for every SKU.

01 / The Tuesday problem
Product Pics was built for the moment a merchandising team receives a folder of flat shots and needs a storefront by the end of the day. There is no canvas to babysit and no scene to rebuild forty times. Define the batch, upload the products, and let the system carry the repetitive work.
Fidelity
Image editing starts from the source photograph, preserving the color, print, texture, logo, and silhouette a shopper expects to receive.
Throughput
Direct-to-R2 uploads and asynchronous generation make the workflow fit a catalog refresh, not just a one-image demo.
Variety
Scenes are deliberately varied across the run so a collection feels photographed over multiple sessions, not stamped from one prompt.
02 / From hanger to homepage
Everything between upload and download is designed to disappear into one reliable batch run.
Choose the wearer, age or age range, and create one working batch.
Upload as many as 100 flat product shots directly to cloud storage.
Every image is normalized, assigned a varied scene, and processed asynchronously.
Retry individual failures, then export every finished image and its report as one zip.
03 / Built like an operator tool
Uploads travel directly to Cloudflare R2. Generation runs asynchronously. Individual failures can retry without poisoning the batch. The result is a narrow tool that stays useful at real catalog volume.
Catalog photography, without the calendar.