Input: SKU CSV, master prompt, and output contract
Output: one approved probe, then batch MP4s and webhook results
Aspect: one platform ratio per batch
Build log
1. Freeze the template
I choose one ratio, one duration, one hook, and one CTA. Batch variables are limited to product reference, color name, and one scene note.
2. Validate one row
I run one SKU through the full check: first, middle, last frame, label, and CTA. A failed probe must stop the batch.
3. Run a small batch
I try 5-10 clips before scaling. At 5 seconds, 10 Seedance 480p clips are 900 credits; 10 Seedance 720p clips are 1,950 credits.
4. Use the API contract
The REST API accepts Bearer auth and webhook callbacks. The free tier allows 60 requests/minute, so I queue rather than send all rows at once.
5. Retry idempotently
I keep an idempotency key and store the returned task ID. A webhook retry checks status first; it does not create a second generation.
Complete execution record
Task boundary and source gate
Treat AI batch product video generation as a deliverable, not a definition. The job receives SKU CSV, master prompt, and output contract and owes one approved probe, then batch MP4s and webhook results in one platform ratio per batch. Write the rejection reason first, then turn it into the first hard constraint.
Do not start until the source photo has a visible product code, a note on material and color, the approved claim, and a named target module. Check packaging damage, sticker state, lighting direction, and background rights before generation. Do not invent certifications, competitor claims, price windows, or a model using the product in an unsafe way. If the seller cannot prove it, the image does not carry it.
The imgmov route
Open Asset Library first, attach the master SKU as the locked reference, then build the module or shot around that reference. Keep offer copy, platform text, and CTA outside the visual prompt. In imgmov, the approved image becomes the source of truth and generation supplies only the requested scene, angle, or motion.
Keep platform requirements outside the model prompt. The prompt can describe a scene; a named checklist records the crop, claim, consent, and console check that make it deliverable.
Lock the variables that cannot drift
Lock product silhouette, label spelling, logo position, material, primary color, accessory count, contact shadow, and the platform safe area. Scene, props, and motion may change; these fields may not.
Put the locked fields at the top of the prompt, not at the end: Validate one SKU before a batch. At 5 seconds, 10 clips cost 100 credits on Agnes Video, 900 credits on Seedance 2.5 at 480p, 1,950 credits at 720p, and 1,950 credits on Kling without audio. The API free tier allows 60 requests/minute; use an idempotency key and webhook task ID for retries. Save that prompt with the reference, ratio, and model so the next run starts from a decision instead of a guess.
Step-by-step build path
1) Freeze the template: I choose one ratio, one duration, one hook, and one CTA. Batch variables are limited to product reference, color name, and one scene note. Leave one checkable artifact from this step; do not start the next until it exists. 2) Validate one row: I run one SKU through the full check: first, middle, last frame, label, and CTA. A failed probe must stop the batch. Leave one checkable artifact from this step; do not start the next until it exists. 3) Run a small batch: I try 5-10 clips before scaling. At 5 seconds, 10 Seedance 480p clips are 900 credits; 10 Seedance 720p clips are 1,950 credits. Leave one checkable artifact from this step; do not start the next until it exists. 4) Use the API contract: The REST API accepts Bearer auth and webhook callbacks. The free tier allows 60 requests/minute, so I queue rather than send all rows at once. Leave one checkable artifact from this step; do not start the next until it exists. 5) Retry idempotently: I keep an idempotency key and store the returned task ID. A webhook retry checks status first; it does not create a second generation. Leave one checkable artifact from this step; do not start the next until it exists.
Change one named variable per rerun: prompt, reference, camera, duration, model, ratio, or export crop. If two variables change together, a better output cannot be reused because nobody knows which fix worked.
Review gates and evidence
Review at 100%. Read small text, count buttons and parts, compare color against the source, inspect the four corners, and overlay the platform crop. A thumbnail is only a concept check, not a marketplace check.
Keep source, approved wording, rejected version, correction, credit cost, and final crop next to the asset. The record exists so the next reviewer can reproduce the decision without a chat thread.
Failure diagnosis and retry ladder
Name the failure first: label redraw, color drift, shape drift, missing accessory, wrong contact shadow, or cropped CTA. Stop prompting for more letters, reduce the variable count, return to the reference, and only then upgrade the model.
Do not upgrade on hope. A 5-second Agnes Video probe is 10 credits. If the concept passes, Seedance 2.5 costs 90 credits at 480p or 195 at 720p for 5 seconds; Kling is 195 without audio or 245 with audio. Veo enters only when a 4/6/8-second cinematic bucket is genuinely worth 80/125/165 credits. Prove hook, subject, and rhythm first, then pay to clean up motion that already worked.
Versioning and handoff
Deliver by module and ratio, not one stretched master. Name files with SKU, module, crop, version, and approval state. Keep the rejected render and the correction line in the same folder.
The folder is boring on purpose: source, approved reference, generation settings, caption file, platform cuts, QA screenshots, and one correction line. A reusable asset is boring in the right way.
Why this is not a generic answer
The imgmov advantage is the chain: Asset Library preserves the subject reference, Canvas fixes shot order and first/last frames, the workspace routes Agnes to Seedance, Kling, or Veo only after proof, and your external editor adds captions and CTA without regenerating the media.
Do not invent certifications, competitor claims, price windows, or a model using the product in an unsafe way. If the seller cannot prove it, the image does not carry it. If the request only asks what ai batch product video generation means, a search page is faster. This page is useful when someone must deliver one approved probe, then batch mp4s and webhook results under real constraints.
Frequently asked questions
What should I validate first?
One SKU and one output contract. If the probe fails, do not start a batch.
The workflow is specific about its stopping point: it starts with SKU CSV, master prompt, and output contract and stops at one approved probe, then batch MP4s and webhook results. In imgmov, upload the source, lock it as a reference, set one platform ratio per batch, run one proof, and save the passing settings. If a reviewer cannot tell which version is approved, the workflow has failed even when the media looks good.
How much does a 10-clip batch cost?
At 5 seconds: 100 credits on Agnes Video, 900 credits on Seedance 480p, 1,950 credits on Seedance 720p, and 1,950 credits on Kling without audio.
Do not upgrade on hope. A 5-second Agnes Video probe is 10 credits. If the concept passes, Seedance 2.5 costs 90 credits at 480p or 195 at 720p for 5 seconds; Kling is 195 without audio or 245 with audio. Veo enters only when a 4/6/8-second cinematic bucket is genuinely worth 80/125/165 credits. Prove hook, subject, and rhythm first, then pay to clean up motion that already worked.
What is the API rate limit?
60 requests/minute on the free tier.
The check is not “does it look AI-nice?” It is: Review at 100%. Read small text, count buttons and parts, compare color against the source, inspect the four corners, and overlay the platform crop. A thumbnail is only a concept check, not a marketplace check. Then the source, approved copy, rejected version, correction, and final crop stay in the same handoff folder.
How do I avoid duplicate charges?
Use an idempotency key and persist the task ID returned with the webhook payload.
Name the failure first: label redraw, color drift, shape drift, missing accessory, wrong contact shadow, or cropped CTA. Stop prompting for more letters, reduce the variable count, return to the reference, and only then upgrade the model. Change one named variable, keep the old version, and record the credit cost. If the same failure repeats, fix the reference or scope rather than asking the prompt for forgiveness.
When should I use 480p?
For social previews and concept batches. Use 720p or 4K for the final client-ready set where the plan allows it.
The imgmov advantage is the chain: Asset Library preserves the subject reference, Canvas fixes shot order and first/last frames, the workspace routes Agnes to Seedance, Kling, or Veo only after proof, and your external editor adds captions and CTA without regenerating the media. The handoff is reusable only when the source, reference ID, prompt, model, cost, rejection reason, and approved cut are linked. That chain is what makes the next ai batch product video generation task faster.