Asia-Pacific, selling into export markets
Private-Label Manufacturer
What AI reads
41 → 83
AI readiness score
What shoppers see
5x
SKU visuals shipped per month
Enterprise · Large catalogs
Make your whole catalog
AI-commerce ready.
The audit and fixes we do for one product, run across every SKU you sell.
More than 10 years with consumer brands
Consumer goods and e-commerce — we've run the catalogues, not just built the software
About ChillaHub- Vitamin C Serum58→ 896Needs workWritten back—Ready
- Daily Trainer Running Shoe49→ 876Needs workWritten back—Ready
- Merino Travel Tee60→ 885Needs workWritten back—Ready
- Ceramic Nonstick Pan 10"51→ 865Needs workWritten back—Ready
- 3-in-1 Wireless Charging Stand64→ 916Needs workWritten back—Ready
- Slow Feeder Dog Bowl42→ 835Needs workWritten back—Ready
- Silicone Suction Plate Set50→ 855Needs workWritten back—Ready
- Insulated Water Bottle 32 oz55→ 845Needs workWritten back—Ready
- Magnesium Glycinate Capsules46→ 826Needs workWritten back—Ready
- Wooden Stacking Rainbow39→ 796Needs workWritten back—Ready
- Compact Standing Desk53→ 816Needs workWritten back—Ready
- Gold Huggie Earrings62→ 905Needs workWritten back—Ready
12 SKUs · sample data
Client stories
Three sellers with catalogs too big to fix by hand.
Challenge
A contract manufacturer launched its own private-label line for export markets: more than 300 SKUs in the first year across home and personal care, and three in-house designers. Its product data came straight from factory spec sheets, written in the words engineers use rather than the words shoppers type. Leadership would not put unreleased designs into public AI tools, so new SKUs waited weeks for images and about 40% of first drafts drifted off the brand and had to be redone.
What we did
We set up ChillaHub inside the manufacturer's own cloud account and trained it on their brand rules and approved photos. Each spec sheet became a product profile with attributes, use cases and FAQs, delivered as import files because nothing could be written into their stores from outside. Designers now make packaging mockups and listing images there, and photos of unreleased products never leave their environment.
What took longer
- The first three weeks of images were inconsistent, because the brand rules were still being written. Output settled once the rules were finished and loaded in.
- Mapping factory material names to shopper language took a round of review with their sales team.
Results
What AI reads
- 41 → 83AI readiness score
- 55% → 96%Attribute completeness
What shoppers see
- 0Assets sent to public tools
- -65%Creative production time
- 5xSKU visuals shipped per month
- +38%On-brand first-pass rate
Southeast Asia, six markets
Marketplace-Native Brand
- Shopee
- Lazada
- TikTok Shop
What AI reads
3/20 → 12/20
Shopper questions where AI suggests them
What shoppers see
-70%
Listing image turnaround
Challenge
A brand that grew up on marketplaces sells on Shopee, Lazada and TikTok Shop in six Southeast Asian markets. Around 9.9, 11.11 and Black Friday, image demand can jump tenfold inside two weeks, and each market wants its own language and price framing on the main image. Freelancers and public AI tools let the look drift between SKUs and markets. Shoppers had also started asking the marketplaces’ AI assistants what to buy, and the brand rarely came up.
What we did
We set ChillaHub up in the brand's own environment with its templates and past campaigns, so merchandisers make main images and detail-page sections from a shared prompt library and reuse a winning look across a product family. We rewrote listings per market with the attributes and questions each assistant looked for, and wrote them back through collaborator access.
What took longer
- Thai and Bahasa headlines still needed a native copywriter to check line breaks before publishing. New creative directions still came from their art director.
- Answers in Thai and Bahasa improved later than English, because there were fewer reviews to work from.
Results
What AI reads
- 3/20 → 12/20Shopper questions where AI suggests them
- +85%Visits from AI assistants
What shoppers see
- -70%Listing image turnaround
- 4xPeak-season throughput
- 18k+SKU visuals per quarter
- -80%Peak-season outsourcing
Asia-Pacific into North America and Europe
Cross-Border E-Commerce Seller
- Amazon
- Shopify
- TikTok Shop
What AI reads
+60%
Orders from AI assistants
What shoppers see
-60%
Localization cost
Challenge
A seller ships from its Asia-Pacific factory base into North America and Europe through Amazon, Shopify and TikTok Shop, and each marketplace and market expects its own look. Regional agencies were slow and expensive, and putting unreleased range plans through public AI tools risked showing them to competitors. In the US and Europe more of its shoppers were starting in ChatGPT and Gemini, where its listings read as thin.
What we did
We deployed ChillaHub privately and trained it on the seller's brand rules, then used it for listing images, ad creative and seasonal campaigns in nine languages. We built one product profile per SKU and turned it into feeds that follow each marketplace's own schema.
What took longer
- Localization was more than translation. A few markets needed their own reference images on top of the shared brand rules.
- Each marketplace names attributes differently, so one profile became three feeds to maintain.
Results
What AI reads
- 52 → 88AI readiness score
- +60%Orders from AI assistants
What shoppers see
- 1Consistent brand voice
- 3Marketplaces with a native look
- 12Markets served
- -60%Localization cost
Client names are withheld at their request. Figures come from the customers' own reporting and are published with their permission.
What a catalog project covers
Catalog audit
Every SKU gets the report from our sample audit, with gaps ranked by what to fix first.
Product data, written back
We fill missing attributes, use cases and FAQs, then write them into Shopify, Amazon or your feed. If you'd rather not give us access, we send a file you can import.
Images at catalog scale
Hero, lifestyle and ad images for each SKU. We change the background and the scene. The product stays exactly as you photographed it.
AI recommendation tracking
Each month we ask ChatGPT and Gemini a fixed set of shopper questions and report where your products come up.
How a project runs
Pilot
US$1,000
Credited in full if you continue
Full catalog
The rest of your catalog, category by category
Ongoing optimization
With AI recommendation tracking
The pilot
- One category, any number of SKUs
- For every SKU: an AI readiness report and rewritten product data
- For up to 10 SKUs: a full set of images
- Two weeks, counted from the day your materials arrive
- Data comes back your way: written into your store with collaborator access, or as an import file (Shopify CSV, Amazon template or feed)
- You work with the people doing the work, not an account manager
Start a pilot
Need a dedicated instance, or everything inside your own AWS or Azure account? We've set that up before.
Start a pilot.
Tell us about your catalog and we'll reply with a pilot scope.
