Automate product photo creation at scale

During ingestion we classify every source file by resolution, aspect ratio, lighting temperature, and background color. Images below your chosen pixel threshold are routed to a super-resolution module trained on retail textures, think knitwear, glossy plastic, brushed metal, so upscaling keeps fine detail rather than introducing blur. Backgrounds are masked with a matting model that separates even complex edges (hair strands, lace trim) before inserting your preferred neutral backdrop or branded color gradient. The end result is a uniform, high-definition set that looks as if it came from a single professional studio session.

Every render passes a defect-detection net that hunts for warped seams, duplicated logos, floating shadows, or limb distortions on model shots. If an artefact is detected, the region is re-inpainted or the entire frame is regenerated. For apparel, garment landmarks (neckline, sleeve, hem) are measured against expected dimensions to catch proportion drift. A random 3% sample per batch is then routed to a trained visual-QA team for human inspection, and their feedback is used to adjust diffusion temperatures and mask weights in subsequent runs, continually shrinking the error rate over time.

Yes. Alongside hero and detail images, you can specify “scene packs” that place the product within AI-generated environments, kitchen counters, workout spaces, outdoor trails, matched to your buyer personas. You choose the ambiance (natural light, urban loft, minimalistic) and the system composes the scene, adjusting camera focal length, depth of field, and prop placement to highlight key selling points. Because all props and backgrounds are also AI-generated, licensing is never an issue, and you receive PSD layers for individual elements in case your design team wants to fine-tune placement.

Before export, each file is validated against a rule set covering Amazon, eBay, Walmart, Zalando, and more than 30 regional marketplaces. Checks include minimum and maximum edge length, mandatory white background for hero shots, no watermarks, centered product bounding box within 10% tolerance, and consistent color profile (sRGB). Files that fail a dimension or weight test are automatically resized or re-compressed, ensuring that 95%+ of images clear marketplace ingestion on the first attempt, dramatically reducing the back-and-forth that slows down listing approvals.

Every generated file is named using a deterministic pattern: [SKU]__[angle|scene|zoom]__[size].jpg. A manifest JSON (or CSV) accompanies the ZIP, mapping each filename to its SKU, image role (hero, lifestyle, detail), and any variant metadata (color, size). Native connectors are available for Akeneo, Salsify, Pimcore, Shopify, and Adobe Commerce: after you drop the archive into a watch folder, the connector reads the manifest, uploads images to the correct asset slots, and updates the PIM record. Webhooks notify downstream systems, marketplaces, CMS pages, so refreshed visuals propagate automatically without manual file handling.