★★★★★
The Checkout Loom team were easy to work with and brilliant at the work itself. I highly recommend them to anyone who needs dependable automation.
IveraAutomation client
Verified
Product content and catalogue automation
Product content and catalogue automation for online stores that keeps every description, title and attribute complete and consistent
Product content and catalogue automation for online stores begins with a plain truth, which is that a catalogue is only as good as the weakest record in it, and that copywriting a thousand products by hand produces uneven descriptions, missing attributes and listings that break the rules of the channel they were pasted into. We build one clean product record, generate descriptions, SEO titles, attributes and translations from it, check every output against the limits of each channel, and publish in controlled batches that a person reviews.
- Fixed price from $2,790, paid once
- Every claim comes from the product record
- Batches reviewed before anything goes live
- Platforms supportedShopify, WooCommerce, BigCommerce, Wix and custom catalogues, with Amazon, Etsy, eBay and Google Merchant Center as output channels.
- Typical storeCatalogues from a few hundred to tens of thousands of products with uneven descriptions, missing attributes or several channels to feed.
- Source dataSupplier spreadsheets, PDFs, manufacturer feeds, existing listings and product photos, combined into one record per product.
- Stores coveredOne catalogue per plan, with extra catalogues, brands and languages available as priced options.
- OutputsDescriptions, SEO titles and meta descriptions, attributes, translations, bulk upload files and marketplace listings.
- Live inThree to five weeks for a pair of services on a starter catalogue and up to twelve weeks for a full programme on a large one.
The costly disconnect
Why catalogues decay even when someone cared about every product at launch
The first fifty products are written with care, and the next five hundred are written to a deadline, so the catalogue ends up with a few excellent pages, a long tail of thin ones and a spreadsheet nobody trusts.
Several versions of every product
The supplier file, the store, the marketplace listing and the ad feed each hold a different title and a different set of attributes for the same product. It is easy to overlook until a busy week exposes it, and by then the cost to online stores is already counted in refunds, hours or lost sales in the automation work in the product content and catalogue automation build.
Thin and copied descriptions
Descriptions pasted from manufacturers rank poorly because dozens of stores publish the same words, and Google treats low-value copied pages as a quality problem. The fix is not more effort but a better rule, and that is exactly what the automation build for online stores puts in place in the product content and catalogue automation build.
Missing attributes that cost sales
Size, material, colour and compatibility are the fields shoppers filter on, and a product without them disappears from filters and from shopping feeds. Many owners only notice this problem when a customer complains, so catching it earlier is one of the quiet benefits of automation for online stores as it applies to product content and catalogue automation.
Channel rules broken by pasting
A title that fits the store breaks on Etsy at 140 characters or on eBay at 80, and marketplace limits are changing, so a paste that worked last year is rejected today. Left alone, this problem repeats with every order, which is why automation for online stores is built to handle it by rule and not by memory for this product content and catalogue automation work.
Updates that take weeks
A new supplier file, a price change or a rebrand means editing hundreds of pages by hand, so the catalogue lags behind the business. It is easy to overlook until a busy week exposes it, and by then the cost to online stores is already counted in refunds, hours or lost sales in the automation work in the product content and catalogue automation build.
Claims nobody checked
Descriptions that say waterproof, organic or compatible without a source create returns, complaints and in some markets legal risk. The fix is not more effort but a better rule, and that is exactly what the automation build for online stores puts in place in the product content and catalogue automation build.
- 140characters is the title limit commonly reported for Etsy listings, against about 80 for eBay, so one title rarely fits every channel.
- 15 MBis the largest product CSV Shopify accepts in one import, which is why large catalogues are split and loaded in batches.
- 1product record should be the single source from which every description, title and listing is produced.
Sources: Shopify product import documentation; Etsy and eBay seller documentation as summarised by marketplace tools, checked at build time; Google guidance on AI-generated content.
What changes in your catalogue once one record feeds every description and listing
Every product has a complete record, the words and fields on each channel come from it and nothing is published unreviewed.
How the catalogue runs today
- Each channel holds its own version of the product.
- Descriptions are copied, thin or inconsistent.
- Attributes are missing or typed differently.
- Updates take weeks of editing.
- Claims in descriptions have no source.
How the catalogue runs afterwards
- One product record is the source for the store, marketplaces and feeds.
- Descriptions are written from the record in a consistent voice with original detail.
- Attributes follow a defined schema and are checked for completeness.
- A change to the record updates every channel in a controlled batch.
- Every claim traces to a field or a supplier document.
What the catalogue report shows
- Fewer returns from wrong claims.
- Better filter and feed visibility.
- Consistent brand voice.
- Faster updates.
- Pages that are worth indexing.
What the system produces
- Merging supplier, store and listing data into one record per product.
- Drafting descriptions, SEO titles and meta descriptions from the record.
- Extracting and normalising attributes such as size, material and colour.
- Checking length, banned terms and required fields for each channel.
- Publishing approved batches and logging every change.
What a person approves
- Approving each batch before it goes live.
- Claims that need legal or technical review.
- Brand voice and the wording of flagship products.
- Which products and channels come next.
- Corrections to the source data.
Which online stores gain most from automating product content and the catalogue
If your catalogue has outgrown the person who wrote it, or you sell the same products in more than one place, the work is repetitive in exactly the way a system does well.
Stores with large catalogues
Hundreds or thousands of products make hand-writing impractical and consistency valuable. Owners in this position often say the biggest change is the time returned each week, and automation is built to deliver that first for online stores for this product content and catalogue automation work.
Stores selling on several channels
One record that produces channel-ready output ends the copy and paste between store and marketplaces. This is the kind of situation where a fixed-price build is easier to justify than a monthly subscription for automation for online stores around product content and catalogue automation.
Stores with frequent supplier updates
New lines and changed specifications flow into the record and out to every listing. We look at this situation in the audit and give online stores an honest view of whether the build is worth doing now or later in the automation work as it applies to product content and catalogue automation.
Teams with one overloaded writer
A first draft from the record turns a writer into an editor and multiplies output. If this describes your business, the automation work for online stores is likely to pay back quickly, and we will tell you plainly if it will not when product content and catalogue automation is the job.
Stores working on SEO
Unique descriptions, clean titles and complete attributes are the basis for search and shopping feeds. Owners in this position often say the biggest change is the time returned each week, and automation is built to deliver that first for online stores for this product content and catalogue automation work.
Stores in regulated categories
Claims checked against sources protect supplements, cosmetics, electronics and children’s products. This is the kind of situation where a fixed-price build is easier to justify than a monthly subscription for automation for online stores around product content and catalogue automation.
The events that start each step of the catalogue pipeline
The pipeline reacts to changes in the product record and to new data arriving, so content never waits for a project.
supplier_file_receivedA supplier file arrives
The file is parsed, matched to existing records by SKU and merged with a log of what changed. A short summary of how often this event occurs appears in the weekly report, giving online stores a clear view of how busy this part of the automation work is for this product content and catalogue automation work.
record_updatedA product record changes
Changes to specifications or price queue the affected descriptions and listings for regeneration. Where the event depends on outside data, the data is checked for freshness first, because a stale figure is worse than no figure for automation for online stores in the product content and catalogue automation build.
draft_generatedA draft is written
The draft is checked against the record for unsupported claims and against the channel for length and rules. Each moment like this has its own rule, so automation for online stores behaves the same way every time and never has to guess what to do next as it applies to product content and catalogue automation.
review_requestedA batch awaits approval
A person approves, edits or rejects each product in a batch from one screen. The event is logged with the rule that handled it, which lets you check later exactly what automation did for online stores and why it did it when product content and catalogue automation is the job.
batch_publishedA batch is published
Approved content is pushed to the store and channels in controlled batches with a rollback copy. Because this trigger is handled separately from the others, a problem with it never delays the rest of the automation work for online stores in the product content and catalogue automation build.
channel_rejectedA channel rejects a listing
The rejection reason is read, the content is corrected within rules and the listing is resubmitted. You decide how much of this runs without approval, and for online stores we usually begin with a review step until the first results look right in the automation work as it applies to product content and catalogue automation.
One product followed from a supplier spreadsheet to a published, checked listing
This shows how raw supplier data becomes a record, a description and a set of channel listings, with a person in the loop.
- 01
The file arrives
A supplier sends a spreadsheet with a new trail pack, and the pipeline matches the SKU, finds no existing record and creates one. The step uses only the facts you supplied, so nothing in the automation result for online stores depends on guesses or on outside sources you did not approve as it applies to product content and catalogue automation.
- 02
The record is enriched
Attributes such as volume, material, weight and waterproof rating are extracted from the sheet and the product photos and normalised. Timing for this step is paced to the limits of your tools, so automation for online stores keeps running calmly even when volume is high as it applies to product content and catalogue automation.
- 03
The description is drafted
The pipeline writes a description using only those facts, in your voice, and notes which sentences came from which fields. A check at the end of the step compares the result with the input, which catches the small mistakes that otherwise surface days later in the automation build for online stores in the product content and catalogue automation build.
- 04
The channels are prepared
It produces a store title, an SEO title and meta description, an Etsy-length title and an eBay-length title, each within its limit. Because the steps are separate, a change to one of them, such as a new rule for online stores, does not disturb the others in the automation flow for this product content and catalogue automation work.
- 05
A person reviews
You see the record, the drafts and any flagged claims in one screen, change one line and approve the batch. The same step is repeated for every item in the batch, so the tenth record receives the same care as the first when automation runs for online stores as it applies to product content and catalogue automation.
- 06
The batch is published
Content is pushed to the store and channels, a rollback copy is kept and any rejection is read and corrected. Anything unusual at this point is flagged in plain words, which saves you from reading logs to understand what the automation work found for online stores for this product content and catalogue automation work.
Pricing
Price your product content and catalogue automation
Choose how many content services to combine, tell us about your catalogue size and channels, and add any extras, and the total and live date update as you go.
What product content and catalogue automation costs and what raises the price
Our fee is fixed and paid once, while model usage and any marketplace tool subscriptions are billed by their own providers.
Catalogue size
Tens of thousands of products need more batches, more checks and more review time. This is one of the factors we price in writing before work starts, so the automation quote for online stores reflects your real situation and not an average as it applies to product content and catalogue automation.
Data quality
Messy or missing source data adds audit and clean-up work before content can be generated. If this factor is small for you, it adds little to the price, and the written quote shows exactly how much it did add for online stores in the automation work when product content and catalogue automation is the job.
Channels and languages
Each marketplace and language adds rules, outputs and tests. You can lower the cost by tidying this part first, and we say so plainly in the plan when the automation work for online stores would benefit as it applies to product content and catalogue automation.
Review requirements
Regulated claims and several approvers add review steps. Anything extra that this factor creates later is quoted before it is built, so the fixed price for automation never grows by surprise for online stores around product content and catalogue automation.
Reporting depth
Completeness dashboards and per-channel reports take extra build time. We explain this factor in the quote in plain words, because online stores should understand what drives the price before agreeing to anything in the automation work in the product content and catalogue automation build.
Ongoing updates
Continuous supplier feeds need monitoring and are an optional monthly service. Changes to this factor after the quote are handled as a written change, with its own price, and never as a hidden charge on automation for online stores as it applies to product content and catalogue automation.
Model usage, marketplace tools and feed subscriptions are billed by those providers.
Next step
Ready to price Product Content and Catalogue Automation for Online Stores?
Product content and catalogue automation for online stores turns one clean product record into descriptions, SEO titles, attributes, translations and marketplace listings, checks each one against channel rules, and publishes them in bulk, so a catalogue of hundreds or thousands of products stays accurate and consistent without a copywriter touching every page.
- One fixed price from $2,790, paid once
- Every claim traced to your own data
- Thirty days of fixes after the first batch
Three more catalogue jobs the same pipeline can do
Because everything flows from one record, adjacent jobs need little extra work.
Translations from the record
Descriptions and titles are translated from the verified record with terminology you approve. Results from this job appear in the same weekly report as the main automation work, giving online stores one place to judge whether it earns its keep for this product content and catalogue automation work.
Google Merchant Center feed clean-up
Titles, GTINs, categories and attributes are checked against feed requirements before submission. We include this idea because owners who run automation for online stores often ask for it within a few months, and it is cheaper to plan for it early in the product content and catalogue automation build.
Seasonal refreshes
Seasonal wording and collection copy are regenerated from the record and approved in a batch. The job follows the same approval rules as everything else, so nothing reaches a customer of online stores without passing the checks you already trust in the automation work around product content and catalogue automation.
Which data the catalogue pipeline reads and where each fact is the source of truth
The pipeline works because every product fact has one home, and the rules for conflicts are written down.
| Store object | Fields we use | Direction | Source of truth |
|---|---|---|---|
| Product record | SKU, title, attributes, materials, dimensions | Created and updated | Catalogue record |
| Supplier data | Specifications, cost, stock, documents | Read and merged | Supplier files and feeds |
| Content drafts | Description, SEO title, meta description | Generated for review | Draft store |
| Channel rules | Length limits, required fields, banned terms | Read before output | Channel rule sheet |
| Published content | Live text and attributes by channel | Written after approval | Store and marketplaces |
| Change log | Field, old value, new value, approver | Written on every publish | Audit log |
Channel limits change, so the rule sheet is kept as a file you can edit and is checked against each marketplace’s current documentation at build time.
Edge cases in catalogue automation that we test before launch
Product data is messy in predictable ways, so we test the messy cases before any batch reaches a live store.
Conflicting data between sources
When the supplier file and the store disagree, the record takes the source ranked highest in your rules and flags the difference. When the case appears, the workflow follows a written rule and records the choice it made, so you can review it afterwards if you wish in the automation build for online stores in the product content and catalogue automation build.
Claims without evidence
A draft that says waterproof, organic or certified without a source field is held for review. If a rule cannot settle the case safely, it goes to you with the record attached, and automation for online stores waits instead of guessing in the product content and catalogue automation build.
Variants and bundles
Variants inherit shared text and keep their own attributes, and bundles list their components correctly. Cases like this are the reason the automation build for online stores includes a trial run, because a tidy example never shows them but real records do in the product content and catalogue automation build.
Units and sizes by market
Measurements and sizes are converted and labelled for each market without changing the record. Your answer to this case is added to the rule table, so the same situation is handled automatically the next time it appears for online stores in the automation work around product content and catalogue automation.
Partial failures in a batch
A batch applies product by product, so one rejection never blocks or corrupts the rest. The weekly report counts how often this case occurs, which tells online stores whether it deserves a better rule or is simply rare in the automation work when product content and catalogue automation is the job.
Discontinued and seasonal products
Retired products are archived with redirects and their content is not regenerated. Nothing about this case is hidden from you: it appears in the log with the date, the record and the rule that dealt with it in the automation build for online stores in the product content and catalogue automation build.
Writing by hand, a generic AI writer and a built catalogue pipeline compared
Writing by hand gives control and does not scale, a generic AI writer scales and invents, and a built pipeline produces content from your record with checks and a human gate.
| By hand | Generic AI writer | Checkout Loom build | |
|---|---|---|---|
| Scales to thousands of products | – | ✓ | ✓ |
| Facts come only from your data | ✓ | – | ✓ |
| Respects each channel’s limits | Partly | – | ✓ |
| Claims checked against sources | Partly | – | ✓ |
| Controlled batches with rollback | – | – | ✓ |
| Cost pattern | Writer time | Subscription | Our build fee plus model usage |
Google does not penalise AI-written text as such, but it does treat many low-value pages as spam, so every description is built from original product detail and reviewed.
How the catalogue pipeline is built and what each part costs
We build around your platform and channels and show the monthly cost of each part beside our fixed fee.
A product record store
A structured table, in your platform’s metafields or a database, that holds every fact with its source. Everything this layer does for automation is logged, so you can see what ran, when it ran and what it cost on any given week for online stores as it applies to product content and catalogue automation.
A language model with rules
A current model that writes only from the record, in your voice, with the claim and length rules checked in code afterwards. We test the layer on your own data before launch, so automation for online stores is proven on real records and not on tidy examples for this product content and catalogue automation work.
Platform import and API
Shopify product CSV and GraphQL bulk operations, WooCommerce importers and REST API, or BigCommerce APIs, used within each platform’s limits. If the layer fails or changes its terms, the handover guide explains how to swap it, so online stores is never stranded by one supplier in the automation work for this product content and catalogue automation work.
Marketplace and feed outputs
Amazon, Etsy, eBay and Google Merchant Center outputs built to each channel’s format and limits. Its role is written in plain language in the handover guide, which means a new team member at online stores can understand it in a few minutes in the automation work in the product content and catalogue automation build.
A review screen
A batch view where a person approves, edits or rejects each product with the sources beside the draft. The monthly price of this layer is written next to our fixed fee before you commit, so the true cost of running automation for online stores is clear from day one when product content and catalogue automation is the job.
Make, Zapier or n8n
The workflow layer that triggers the pipeline, retries failures and writes the audit log. You can replace this layer later with another tool, because the rules live in a table you own and are not locked inside any one product in the automation build for online stores when product content and catalogue automation is the job.
How we keep catalogue content accurate and safe to publish
Accuracy matters more than speed in a catalogue, so checks run before publishing and rollback is always available.
Claims traced to fields
Every statement in a draft is checked against a field or a document, and unsupported ones are held. Because this protection is written as a rule and not as a habit, it keeps working when staff change or the business gets busier in the automation build for online stores around product content and catalogue automation.
Rollback copies
The previous version of every changed product is stored so a batch can be reversed. When something goes wrong in automation for online stores, the failure is named, retried within safe limits and listed for you, instead of vanishing into a log nobody reads for this product content and catalogue automation work.
Throttle-aware batches
Batches are sized to platform limits, such as the 15 MB Shopify CSV cap, and retried after throttles. This safeguard runs on every batch and not only on a schedule, so a problem in automation is caught before it can spread to the next record for online stores for this product content and catalogue automation work.
Alerts that name the product
Each alert gives the SKU, the channel and the reason. Each alert names the rule, the record and the next step, which means you can fix the cause from the message alone without opening any tool in the automation build for online stores when product content and catalogue automation is the job.
A trial batch first
A small batch is published and checked on the live store before the full catalogue follows. We compare the results of automation with your own records on a regular basis, so a small drift for online stores is repaired before it becomes a large one in the product content and catalogue automation build.
Owner explanations in writing
Any problem in the first month is explained to you in writing with the cause and the fix. If a check fails, nothing is sent or changed for that record, and it waits in a short list for you, because a delay costs less than a wrong action in the automation build for online stores when product content and catalogue automation is the job.
Permissions, privacy and intellectual property in catalogue automation
Catalogue work touches supplier data and your brand’s words, so access is narrow and ownership is clear.
Least-privilege access
We request the narrowest store and channel access that lets us read products and publish approved batches. We keep no copy of your keys, records or customer details in systems that belong to us, and the handover guide shows you how to confirm that in the automation build for online stores around product content and catalogue automation.
Your content, your ownership
The words produced are yours, and we do not reuse your catalogue or voice for other clients. Only the fields that automation needs are read, and only for as long as the task takes, which keeps the exposure for online stores as small as it can be as it applies to product content and catalogue automation.
Keys in your accounts
API keys sit in your accounts and can be revoked whenever you choose. Every access is logged in your own accounts, so you can see who or what touched a record and when, without asking us for a report in the automation build for online stores when product content and catalogue automation is the job.
Supplier data kept private
Cost prices and supplier terms are never placed in public descriptions or sent to the model unless a rule needs them. If a key is ever lost, it can be replaced in minutes without rebuilding the automation work for online stores, because the rules do not depend on it as it applies to product content and catalogue automation.
Respect for source copyright
We rewrite from facts and never copy another seller’s text. The arrangement is reviewed at the end of the month of corrections, and any access that is no longer needed is removed in writing in the automation build for online stores as it applies to product content and catalogue automation.
Clean exit
You receive a list of every connection we made, and we remove our own access when we finish. Customer details are never used to train outside models, and drafts for online stores are built only from the facts and records you supply in the automation work as it applies to product content and catalogue automation.
What you receive with your product content and catalogue build
Each plan ends with a clean record, working pipelines and the notes to run them.
- A structured product record with a field list, sources and completeness score.
- Supplier file import with SKU matching and a change log.
- Description and title generation in your brand voice from the record.
- SEO titles and meta descriptions within search and platform limits.
- Attribute extraction and normalisation to a schema you approve.
- A review screen for batches with sources beside each draft.
- Channel outputs and rule sheets for the channels in your plan.
- Rollback copies and an audit log for every publish.
- Thirty days of fixes after the first full batch goes live.
Verified client reviews and the quality rules behind our catalogue builds
The unedited words of verified clients of the Checkout Loom team appear below, followed by the rules every catalogue build follows.
- 100%of claims in a draft are traced to a field or a document before it can be approved.
- 1record per product is the source for every channel output we produce.
- 30 daysof fixes follow the first full batch so the pipeline settles before we step back.
Quality rules follow Google’s guidance on helpful content and the platform documentation named above, and are confirmed again at build time.
★★★★★
Everything was configured exactly as discussed, and the team made sure the automation was stable before delivering it. It has been a huge time-saver for our whole team, and it runs without any manual work.
BellamyUnited States
Verified
★★★★★
This was excellent automation work, and it is clear that the team has strong experience with AI and automation. I highly recommend the Checkout Loom team to other businesses.
FinnUnited States
Verified
★★★★★
I am genuinely impressed with the work the Checkout Loom team did on my AI and automation project. They are extremely professional, skilled, friendly and easy to work with, and I am delighted with the final result.
DavidUnited States
Verified
★★★★★
The Checkout Loom team built an automation that simplified my workflow and worked perfectly from day one. Communication was excellent, delivery was fast, and I would happily recommend the service.
RebeccaUnited States
Verified
★★★★★
They set up my automation remarkably fast and executed everything perfectly. Communication and service were top tier, so I could not be happier with the results and I highly recommend the Checkout Loom team.
AbbieGermany
Verified
★★★★★
The automation was set up in a clean and practical way by the Checkout Loom team. It saved me a lot of manual work and made the whole process much easier.
JanoUnited Kingdom
Verified
★★★★★
I highly recommend ordering from the Checkout Loom team. I had slow responses and poor communication with other providers, but this team was great and I am very happy with their service.
HarmetUnited States
Verified
★★★★★
I am a returning customer because my first AI automation workflow worked so well. Once again everything was built exactly as requested, and the whole process was reliable from start to finish.
WilliamUnited States
Verified
How the catalogue build runs from data audit to a published first batch
We audit the data before writing anything, because the quality of the record decides the quality of everything produced from it.
- 01
Audit the catalogue
We export your products, measure completeness by field and find duplicates, conflicts and missing sources. The time this step takes depends on how quickly your records and answers arrive, and we tell online stores early what we need to keep moving in the automation work around product content and catalogue automation.
- 02
Design the record
We agree the fields, the source ranking and the claim rules with you in writing. We use plain language in every document from this step onward, so anyone at online stores can read the plan and understand it in the automation work in the product content and catalogue automation build.
- 03
Build the pipeline
We build the import, enrichment, drafting and checking steps against a test copy of your catalogue. A short summary of the step is added to the handover guide, so the way automation was built for online stores is never lost in the product content and catalogue automation build.
- 04
Write the voice rules
We agree your voice with examples of your best pages and test drafts until they sound like you. You see the result of this step in writing before the next one begins, which keeps the automation build for online stores on schedule and under your control when product content and catalogue automation is the job.
- 05
Publish a trial batch
We publish a small batch, check it on the live store and channels and fix what we find. If this step shows a problem, we say so at once and propose the fix, and the date for automation is moved in writing rather than quietly for online stores for this product content and catalogue automation work.
- 06
Run the full catalogue and hand over
We process the rest in batches and hand you the guide and the log with a month of fixes. Nothing in this step touches your live customers, so online stores can review it calmly and ask for changes before anything goes public in the automation work in the product content and catalogue automation build.
Estimate the writing time a catalogue pipeline could save
Enter the size of your catalogue and the time each product takes and the estimate shows what the share the pipeline drafts is worth.
Hours of writing saved–
Value of that time–
Hours still spent on review–
Review time is included in the final figure at five minutes per product, and the value uses your own hourly cost.
Product content and catalogue automation questions, answered in full
These are the questions store owners ask about quality, channels, Google, accuracy and cost before they order catalogue automation.
What is product content and catalogue automation for online stores?
It is a pipeline that builds one clean record per product and produces descriptions, SEO titles, attributes, translations and marketplace listings from it, checks them against channel rules and publishes approved batches to your store and channels.
Which content services can be combined?
You can combine product description writing, listing optimisation, SEO titles and meta tags, product page generation, bulk upload, translation and data enrichment, and we recommend the order from your catalogue audit.
Will Google penalise AI-written product descriptions?
Google has said AI-generated content is not banned as such, but producing many pages without adding value can violate its scaled content abuse policy. We write from original product detail in your record and review each batch, which is the opposite of mass-produced filler.
How do you stop the system from inventing product claims?
Drafts may use only facts from the record, every statement is traced to a field or a document, and any claim without a source is held for a person before publishing.
Can it keep listings within marketplace limits?
Yes, titles and fields are checked against the limits for each channel, such as the commonly reported 140 characters on Etsy and roughly 80 on eBay, and Amazon’s title rules, which have been changing, are checked at build time.
How are large catalogues uploaded safely?
Batches are sized to platform limits, such as the 15 MB cap on Shopify product CSV imports, a small trial batch goes first and every changed product has a rollback copy.
Will it sound like my brand?
We agree your voice with examples of your best pages, test drafts until they match and keep a voice guide the pipeline follows, with a person approving each batch.
Can it work with supplier spreadsheets and PDFs?
Yes, spreadsheets are matched by SKU, PDFs and images are read for specifications, and conflicts between sources are resolved by the ranking we agree with you.
When will the first batch be live and what do you need from me?
A pair of services on a starter catalogue is usually live in three to five weeks. We need an export of your products, supplier files, examples of your best pages and read access to your store and channels, and we send a written checklist after you order.
What will model usage and channel tools cost me on top of the build fee?
Our fee is charged once, while language model usage and any marketplace tool subscriptions are billed by their providers, and we estimate that monthly cost in writing for your catalogue size.
Give every product a complete record and every channel the content it needs
Choose a plan in the pricing calculator and continue to checkout, or request a quote with your store address, the number of products and the channels you sell on. We reply in writing within one working day with a confirmed start date and a short checklist, so the catalogue audit begins straight away.
- One fixed price from $2,790, paid once
- Every claim traced to your own data
- Thirty days of fixes after the first batch