Which image stacks need attention?
Read live slot coverage, missing views, replacements, and policy risks across the catalog you choose, then prioritize the next useful image instead of checking PDPs one by one.
See Amazon Agent IrisSolutions · product imagery
Keep every image stack accurate, complete, and on-brand.
Ground every image decision in the product data and image stack Amazon is serving through the Selling Partner MCP, then use Amazon Agent Iris to prepare, check, and hold accurate candidates for review.
Aug 1 Aug 4 Aug 7 Aug 10 Aug 13
Complete image-stack coverage · 91% of 428 ASINs · 23 replacements detected · Aug 1–14, 2026
How the work changes
Every candidate starts with the product Amazon is actually selling.
Kuudo reads the live listing and image stack, works from real product material, and prepares only the missing or corrected views your catalog needs. Identity, policy, destination, and approval stay attached from source to publish.
Did Amazon replace an approved image?
Compare the live slot with the approved stack, see when the difference appeared, and review the source and product identity before choosing a response.
See the live catalog connection
Can it work from the real product?
Ground candidates in your product photography and live facts while checking shape, color, quantity, logos, labels, and included contents against the source.
Read the Iris documentation
Will it catch policy problems?
Catch avoidable technical and policy failures before submission, keep every verdict visible, and leave Amazon's final acceptance decision accurately framed.
See image checks in Iris
Does our team approve each destination?
Review the real source, candidate, checks, intended Amazon slot, and publishing state together. Nothing is submitted until the configured approval is present.
Review available image actions
What if the catalog data is wrong?
An accurate image cannot repair a contradictory title, attribute, pack count, or variation. Route the underlying product-data conflict to listing optimization first.
See the listing optimization handoffMake it yours
Bring live catalog health and creative review into one workspace.
Choose the coverage standard, required views, brand checks, and review roles. Keep each candidate tied to real product material and the current Amazon destination instead of passing anonymous files between tools.
See image health across the catalog Live catalog
Find thin stacks, changed slots, and policy risks across the selected ASINs. Each row identifies the next useful view without inventing a conversion claim.
See how Iris handles image work
Review the source, candidate, checks, and slot together
Live product facts constrain the creative work. If those facts conflict with the source image, the workflow stops and sends the catalog correction to listing optimization.
See listing optimizationWhere it runs
Use the client your imagery team already has open.
Live Amazon context, real product sources, image checks, and approval state stay consistent across chat, agent, workflow, research, and IDE clients.
/chat
ChatGPT
Ask which stacks are thin or changed and review candidates beside the live product context.
View quick start
/chat
Claude Desktop
Inspect sources, identity checks, policy verdicts, and target slots through the same scoped connections.
View quick start
/agent
OpenClaw
Hand off recurring image-health checks while every public image submission remains behind approval.
View quick start
/workflow
n8n
Schedule catalog monitoring and route candidate reviews into the creative workflow your team already runs.
View quick start
/ide
Codex
Maintain brand-specific image rules and asset workflows beside the code that governs them.
View quick start
/research
Perplexity
Investigate catalog image questions from private live context instead of inferring from public results.
View quick start
Frequently asked questions
Questions from Amazon imagery teams.
How live listing context grounds new assets, what gets checked, and what always waits for review.
Does this replace our creative team?
No. It gives the team a repeatable workflow for catalog health, candidate creation, checks, and approval. Your creative owner still decides what represents the product and which asset belongs in each Amazon slot.
Can it detect when a live image changes?
Yes. It can compare the live image stack with the set your team approved and identify an unexpected replacement, missing view, or changed destination slot for review.
Can it work from our real product photos?
Yes. Candidates start from product photography you supply and facts from the live listing. The workflow is designed to build from real product material, not invent features, accessories, labels, or claims.
Will it preserve product identity?
It checks product shape, color, quantity, labels, logos, and included contents against the source material and listing facts. Human review remains required because automated checks cannot detect every form of visual misrepresentation.
Does a policy pass guarantee Amazon will accept the image?
No. Policy and geometric checks reduce avoidable rejection, but Amazon makes the final acceptance and display decision. Kuudo keeps the verdict, caveats, and publishing state visible instead of calling a checked image guaranteed.
What if the image conflicts with the title, pack count, or variation?
The underlying catalog conflict routes to listing optimization. Another generated image cannot repair contradictory title, attribute, quantity, or variation data, so the product facts get corrected first.
Can the workflow use SQP, Ads, or returns signals?
Yes. Search Query Performance, Ads, and returns signals can help prioritize which listing or view deserves attention while the live product facts and approved source material continue to constrain the asset.
Guides
See how live product data becomes a reviewable image set.
Start with real product material, check identity and policy, route catalog conflicts correctly, and publish only the candidates your team approves.
Seller · Listings
Rebuild Your Listing Images From Your Own Photos
Seed new Amazon listing images from your own photos, grade each against Amazon's image rules, and approve before anything publishes, grounded by Atlas.
Thomas Spicer
11 min read
Seller · Listings
Listing Suppression Diagnosis: Stranded or Buyable
Use live listing status, the suppression reason report, and FBA evidence to diagnose a silent ASIN before applying the wrong fix.
Thomas Spicer
7 min read
Vendor Central · Operations
Automate Vendor Listing Quality at Catalog Scale
Vendor listing quality stalls on judgment, not mechanics. See how an agent resolves per-product-type schemas and writes through the Listings APIs.
Thomas Spicer
11 min read
The bottom line
The image on Amazon should still be the image your team approved.
Monitor every selected stack, prepare missing views from real product material, and give your team the source, checks, destination, and publishing state in one review.