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Shop the editA reviewable plan for very large catalogs
Batch Processing Product Photography for 1000 Items
A thousand product photos is a logistics problem, not a single button. Every image needs a human preservation check before it leaves the queue, because AI scene editing can quietly change packaging, color, count, or label text. Product Ad Pack handles large catalogs by splitting them into reviewable batches, where each file stays an isolated job with its own state, retry, and export name.
- No card for the first preview
- Copy stays editable
- Product review stays visible
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Shop the edit1approved source photo
2reviewable AI directions
4ready-to-compose ad ratios
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Build a reviewable product-image batch
Choose up to 20 product photos. Each file becomes an isolated job with its own status, preview choices, retry, and commercial export.
Per-product queue
Review every SKU independently
A failure or rejection affects only that product. Ready directions can be opened below without restarting completed jobs.
Preservation review
Compare the source with each direction
Reject any preview that changes packaging, shape, handles, count, color, material, or label text. The original-photo option remains available below.
Four placements
Review the complete ad pack
Change the headline or brand color above and the canvases update without another AI generation.
Free downloads are for evaluation. A paid credit is required for commercial ZIP delivery.
Large catalogs without an opaque bulk button
Batch processing product photography you can still review
Split 1000 items into reviewable batches
The batch workflow accepts up to 20 source files per browser batch, so a 1000-item catalog becomes 50 reviewable passes instead of one unverifiable bulk operation.
Keep one isolated job state per product
Selected, submitting, queued, generating, ready, and failed states stay visible per file. A failed request does not pretend the whole catalog succeeded, and you retry only the affected item.
Export with SKU-oriented filenames
The product or SKU name you provide becomes the base for every ratio, so a 1000-item handoff stays predictable instead of renaming files after the fact.
Why 1000 items is a process problem, not a single click
The temptation with a large catalog is to look for a bulk button that turns every image over to a model and returns 1000 finished ads. That approach fails at the review step. Product photography supports a purchase decision, so a changed bottle label, an extra accessory, a shifted color, or a wrong item count is not a cosmetic error; it is a misrepresentation a buyer may not catch until after they order.
The safe unit for batch processing is the reviewable batch. Product Ad Pack limits a browser batch to 20 source files, and it records each product as a separate job with its own state. That means a 1000-item catalog is worked as 50 batches of 20, and one failed generation never silently spoils the whole run. The cost stays visible because each completed product pack is one paid credit.
Prepare source photos so the batch can be reviewed
Before generating, standardize the inputs. Use one product per file, keep a clear silhouette, and leave enough space around the edges so the scene editor does not have to guess at a cropped handle or lid. Name each file with an ASCII SKU such as linen-tote-01.png; the filename becomes the base for the four export ratios. Confirm you have the right to process each image before upload.
Consistent inputs reduce cleanup later. A sharp PNG, JPEG, or WebP under 8 MB is accepted, and the browser rejects unsupported types or oversized files before anything is sent. When the same product comes in several colorways, photograph each variant separately rather than asking the model to infer the others from one image.
Run, review, and export in reviewable slices
For each 20-file batch, apply one shared campaign brief: the scene, brand color, and offer headline. Then open each product individually. Compare the generated direction with the source and reject any preview that changes packaging, color, quantity, controls, dimensions, materials, or label text. A failed request keeps its job record, so you can retry the affected SKU without spending again on the products that already passed.
The approved direction is composed into four placements: 1080 × 1080, 1080 × 1350, 1080 × 1920, and 1920 × 1080. Free PNG previews are for evaluation; a named commercial ZIP requires an account and a paid pack credit. Working 1000 items this way keeps each export reviewable and each filename predictable, which is what makes a large-catalog handoff dependable.
A three-step plan for 1000 items
Prepare, batch, and review by SKU
- 01
Prepare one product per file with an ASCII SKU
Use a PNG, JPEG, or WebP under 8 MB with one clear product and room around its edges. Name each file with the SKU or product handle so the filename survives the trip.
- 02
Apply one campaign brief per batch
Set the shared scene, brand color, and headline once, then open each product individually to approve or reject the generated direction against the source.
- 03
Review, retry, and export by SKU
Reject any preview that changes packaging, color, count, or labels, retry isolated failures, and export a commercial per-SKU ZIP only after review.
Clear answers before checkout
Frequently asked questions
Can I process all 1000 product photos in one click?
No, and that is deliberate. The browser batch accepts up to 20 source files at a time, and every generated direction still needs a human preservation check. A one-click 1000-item job would hide the product drift that review is meant to catch.
How many credits do 1000 products need?
Each completed product pack spends one credit, so 1000 products need 1000 pack credits. The free daily preview is one anonymous pack per day for evaluation. Plans, pack sizes, and subscription credits are listed on the pricing page, which stays authoritative.
What file names should I use for 1000 items?
Use one ASCII SKU per file, such as linen-tote-01.png. That name becomes the base for the square, portrait, story, and landscape exports, so the output can be handed off or uploaded without renaming.
Will the batch keep every product detail accurate?
No AI scene editor can guarantee that. Check each preview for packaging, color, quantity, dimensions, materials, and label text against the original, and reject any direction that drifts. A confirmed system failure releases the reserved credit; a completed image you reject is not treated as a system failure.
Try the real workflow
Start with one reviewable batch of 20
Prove preservation on a real product before you commit a 1000-item queue.
Create a free pack