Amazon-compliant AI product images: white-background discipline, gallery-scale depth
Amazon's main image is the most regulated image in ecommerce: pure white background (RGB 255,255,255), the product filling at least 85% of the frame, one unit shown front-on, no props, text, logos or watermarks — and at least 1,000px on the longest side or your listing loses zoom (2,000px+ recommended, 10,000px max, JPEG preferred). The secondary images are where the sale actually closes. Berrys generates that full sequence — feature callouts, scale shots, lifestyle, packaging — from your real artwork, identical geometry across every child ASIN.
Each child ASIN keeps its own image set — a consistent family look lifts cross-click
Free Browser Tool
Check your cover photo against Amazon FBA brands rules
Test your packshot cover image for solid white background (#FFFFFF), product frame-fill percentage and 1:1 aspect ratio before uploading to Seller Centre.
Models produce 'studio backgrounds' that land at RGB 250–254 or carry gradients and soft-shadow washes that fail the pure-white check and get suppressed from search. The fix is an export step that normalizes the background to true 255,255,255 — a locked canvas recipe, not a prayer.
85% fill is a math problem
Zoom, mobile SERPs and comparison shopping all punish a product floating small in frame. Berrys recipes output at defined frame-fill ratios: generate once, hold 85–88% consistently across the family.
Zoom magnifies every fake pixel
Buyers zoom to inspect labels at 2,000px. Upscaled or hallucinated text smears under that lens and converts to returns. Artwork-locked generation keeps label edges native-sharp because the text comes from your files.
Variant consistency beats individual beauty
Search shows your catalog as a grid of yourself. Drifted lighting between a 500ml and 1L render reads as two different brands. One workflow, many SKU nodes, zero drift.
How Berrys runs the Amazon image stack
Artwork-first pipeline
Real dielines and pack shots feed the SKU node; composition, scene and lighting are generated around true geometry — the product is never re-imagined.
Infographics on the canvas
Feature callouts and comparison tables live as node compositions next to the imagery: change a claim or bullet, re-render the whole set. No designer queue, no version drift.
A+ module branch
The same node graph outputs wide-format crops sized for A+ modules, keeping the PDP visually unified with the gallery.
Production workflows in Berrys Canvas
Workflow 1
Pure-white main image master (RGB 255,255,255)
1. File Node: Load raw product packshot.
2. Brand System Node: Enforce strict RGB (255, 255, 255) pure white background and 85% frame fill rule.
2. Brand System Node: Apply brand typography and comparison table layout.
3. Image Node (Flux 3): Export wide-format 970×300 and 970×600 banner crops for A+ modules.
Berrys Plugins · Model Context Protocol (MCP)
Create in chat. Keep it on your canvas.
Already working in an AI agent? Connect Berrys to Claude, Cursor, ChatGPT, Codex, or Hermes. Your agent plans the amazon fba brands suite and runs the shots on your Berrys canvas, with saved Brand Memory and credit approval in chat.
Using Berrys, build an Amazon G1881-compliant 7-image sequence for my product reference in ./assets:
1. File node: Load master packshot.
2. Brand System node: Set pure white background RGB (255,255,255). Lock bounding box to 85% of frame with zero props or text.
3. Image node (Nano Banana 2.1): Render 2048×2048 JPG master for zoom enablement.
4. Secondary images: Generate 45° angle, macro texture zoom, scale cue with hand/phone, and contextual lifestyle scene.
Estimate credit cost and request approval before generating.
Amazon's main image must be a realistic, professional product image on pure white — no illustrations, mockups, text or props — and accuracy is on the seller. The durable approach is what Berrys is built for: your real packshot as the truth source, AI for the surrounding sequence (angles, scenes, infographics), human QA before upload. Generated imagery that embellishes contents, scale or accessories is a suppression and suspension risk, not a shortcut.
When NOT to use AI generation for this
Any main image that departs from a realistic representation of the item actually shipped
Categories whose style guides require photography for the main slot — shoot those, use Berrys for the rest of the stack
Inventing scale, bundle contents or certifications the physical product can't back up
Frequently asked questions
Does Amazon allow AI-generated product images?
Amazon's published rules focus on accuracy and presentation: images must realistically and accurately represent the product, and main images must be photorealistic on pure white with no graphics, text or props. There is no blanket 'AI ban' — the bar is truthfulness and spec compliance, which is exactly why Berrys generates from your real artwork and normalizes to spec. Where a category's style guide calls for photography specifically, keep a physical shot for that slot. Rules change by category; verify in Seller Central.
How do I hit the 85% frame-fill rule?
Generate with a defined crop ratio in the workflow instead of cropping by eye: Berrys recipes lock the product bounding box to 85–88% of frame across every image in the family.
Can it keep labels sharp at zoom?
That is the point of referencing real artwork through File nodes: label typography comes from your files instead of being redrawn, so 2,000px zoom shows your actual print.
Does it support A+ content imagery?
Wide crops and module compositions come from the same node graph as the gallery, so the PDP keeps one visual system.
Start free on Berrys Canvas — 50 credits, no card required — or send Berrys Studio a brief and get finished campaign visuals with agency art direction.