Paste a supplier product. CatalogAI returns a full bilingual listing — Thai and English titles, short and long descriptions, ten search keywords per language — in the voice of any brand you run. Under fifteen seconds, every time.
If your team onboards more than a few hundred new SKUs a month, you've felt at least one of these. CatalogAI is built for all three.
A copywriter rewrites every line. Thai first, then a junior translates. Two languages, two passes, four-week backlog. The new range misses launch.
Tops should sound warm. Power Buy should sound technical. In practice, one writer covers both and they read identical. The brand difference goes flat at the catalog level.
EN keywords get auto-translated to TH. The result reads like a textbook — none of the colloquial terms a Thai shopper actually types into the search box. Conversion suffers.
The cards marked ★ ONLY CATALOGAI are features that, to our knowledge, no other catalog or PIM-AI product on the market currently ships in this exact shape. Each one is something we built because the retail-content workflow demanded it — not because a feature comparison sheet asked for it.
Title, short description, long description, and ten keywords — generated in parallel for both languages, not back-translated. Western PIMs translate as an afterthought. CatalogAI writes in Thai and English at the same time, with parallel meaning, not literal translation.
Tops warm and food-expert. Power Buy technical and spec-forward. Central aspirational and elegant. Thai Watsadu practical and builder-friendly. The same SKU runs through all four voices in one screen — the reader sees the difference before they read the brief.
No queue. No async worker. No "we'll email you when it's ready." A full bilingual listing returns inside the same HTTP request, while the reviewer is still on the page. Speed is the demo — and the difference between "interesting tool" and "shipped tonight."
Ten Thai keywords per SKU including the informal, colloquial terms Thai shoppers actually type — not back-translated English. Catches the gap between "Spaghetti Strap Polka-dot Dress" and what someone really searches for at 11pm in Bangkok.
A single POST /generate call returns clean JSON. No auth header for evaluation. Your team can curl it inside a meeting and integrate against it the same week. CatalogAI does not replace your PIM — it sits beside it, generating the copy your PIM stores.
Two intake paths in the demo. Paste raw supplier text into the textarea, or pick from the seeded sample SKU dropdown. The first line of the paste becomes the product name; the rest is treated as supplier context.
Switch the voice dropdown. The same product re-generates in the new tone. Side-by-side comparison is one click. Useful when a category sits across two of your store brands and the merchandiser needs to see both reads.
The home page is not empty. It opens onto 100 pre-generated examples across all four voices, searchable, filterable. The reviewer sees the system working at scale before they type a single character.
A structured-output schema is enforced server-side at the AI provider. No "sometimes the model adds commentary" — the response is parseable on every call.
The voice prompt is told never to invent specs, certifications, or claims that aren't in the input. Missing facts get worked around, not made up. (Stronger guardrails are post-pilot scope.)
Every result card carries the live wall-clock generation time in monospace. The reviewer sees "7.4s" — speed becomes a visible artifact, not a claim.
Four pre-configured voices ship in the demo. Editable voice admin and tenant-specific voice tuning are deferred to post-pilot scope.
Every box below is a real screen in CatalogAI. Every arrow is a real action your team takes. Find the workflow closest to yours — that's how you'll use it on day one.
Organisations like: Central Retail (Tops, Robinson, Power Buy, Thai Watsadu), The Mall Group, Tang Hua Seng — any retailer running two or more store brands that each need their own copy register.
Pastes the supplier sheet for the new range. Picks the store brand it sits under.
Returns TH + EN title, short, long, and ten keywords each. In the Tops voice.
Switches voice to Power Buy. Same SKU regenerates for the electronics chain.
Copies JSON into the PIM. Ships to Tops Online and Power Buy Online same day.
Organisations like: Lazada Thailand, Shopee Thailand, JD Central — the teams that bring third-party sellers onto the platform and need their listings cleaned up before they go live.
Drops the seller's PDF spec sheet. The model reads it directly.
Pulls brand, name, specs. Generates the bilingual listing.
Reviews ten Thai keywords. Approves the informal forms shoppers actually type.
Pushes JSON into the marketplace catalog. Listing goes live the same shift.
Organisations like: HomePro, Dohome, Index Living Mall, B-Quik, Office Mate — retailers running tens of thousands of SKUs across deep categories where every product needs technical, accurate copy.
Drops a CSV row with model number and dimensions. CatalogAI parses it.
Generates technical-tone copy. Specs surface in the title and short description.
Reviews five SKUs in parallel. Each card carries its generation time and voice.
Exports the bilingual JSON bundle. Hands off to the existing PIM pipeline.
Organisations like: Makro, Foodland, large foodservice distributors — operators that take in supplier batches every week and need fast, consistent listings for their B2B and online catalogs.
Drops a batch of CSV rows. The team queues them in the browser.
Browser fires 12 parallel calls. Cards fill in live as each SKU completes.
Spot-checks five at random. Flags one for re-voice. Approves the rest.
Pulls the batch JSON. Pushes into the wholesale catalog and online channel.
CatalogAI is built first for Thai retail — multi-brand groups, marketplaces, and large-format chains — and then for everyone else. The list below is what you would otherwise spend three months bolting onto a generic Western catalog tool.
Copy reads like a Thai shopper would actually type and read — not translated-feeling Thai. The voice prompt anchors register, vocabulary, and rhythm to native usage.
English tells the same product story but reads native to English shoppers. The model is instructed never to back-translate Thai phrasing word-for-word.
Four pre-configured voices map to Thailand's actual retail tiers: hypermarket, electronics chain, premium department, builder hardware. Each voice is locked, not user-edited, in the demo.
The keyword pass explicitly includes colloquial and informal forms — the way Thai shoppers type into a search box, including katoey-language and shorthand spellings.
Titles always lead with brand or product name and surface one key spec — size, model, weight, flavour, material. The pattern Thai retail catalogs already use.
The voice prompt is explicit: never invent specs, certifications, awards, or claims that are not in the input. Missing facts are worked around, not made up.
Default Singapore-region for cost. Thai-region available on request for groups with data-residency requirements on supplier or shopper data.
CatalogAI does not replace Akeneo, Salsify, or your in-house PIM. It generates the copy your PIM stores. The integration is a single API call your dev team can add in a sprint.
Here's what changes in the first onboarding cycle for a typical category team handling 200–500 new SKUs a month across two or more store brands.
Manual bilingual copy by a writer takes a half-hour. CatalogAI returns the same eighteen fields synchronously, in one HTTP request.
A single human writer cannot hold four distinct brand voices across thousands of SKUs. CatalogAI does — every SKU, every batch.
No more back-translation drift. Thai and English are generated together with parallel meaning and native register on both sides.
A supplier batch that used to take a copy team a week now finishes inside a single shift, with consistent voice across the whole batch.
In operational terms, a category team with 300 SKU intakes a month moves the bilingual-copy stage from a two-week bottleneck to a same-day step — freeing the copywriter for editorial work, brand campaigns, and the manual edits AI cannot do well. In financial terms, the unit economics shift from "copy cost per SKU" to "review cost per SKU," which is roughly an order of magnitude lower. In commercial terms, the new range hits the shelf and the search index when it was supposed to.
Figures are derived from MVP-build estimates and our founder's prior enterprise delivery of catalog and content systems for Southeast Asian retailers (2017–2026). Individual results vary by SKU complexity, supplier-data quality, and how heavily your team currently relies on translation rounds. No CatalogAI customer pilot has completed as of the publication date of this page.
Most teams are running their first real supplier batch through CatalogAI by week 6. Here's what each phase looks like at one category line of a few hundred SKUs — additional categories or brands compound onto this baseline.
Voice profiles tuned to your store brands. Sample SKUs loaded from one of your real categories. The team's API key issued and the open endpoint stood up in your environment.
Buyers and copy reviewers using CatalogAI for everyday intake. We sit alongside the team, watch the workflow, and tune the voice prompts based on the actual edits your reviewers make.
Run a real supplier intake batch through CatalogAI end-to-end. JSON exports flow into your PIM. Your category lead reviews the output to confirm it's launch-ready.
Your team operates CatalogAI day-to-day without daily support. We monitor and respond to issues in the background, and start the conversation about additional brands, categories, or languages.
Investment is sized to the number of voices, the volume of SKU traffic, and any custom integration to your existing PIM — discussed in person or on a call when we meet, not on a public price list. Per-SKU API economics and any tenant-specific voice tuning are scoped together at pilot kickoff.
No. CatalogAI generates the bilingual brand-voice copy that your PIM stores. It sits alongside Akeneo, Salsify, or whatever in-house PIM you run — one API call from your existing pipeline, JSON in, copy out. We do not pretend to be a product information management system, and we do not ask you to rip yours out.
By default, the hosted version runs on Singapore-region infrastructure for cost reasons. For Thai retailers with data-residency requirements on supplier or shopper-related fields, we offer a Thai-region managed-tenant option — specify residency at pilot scoping. We do not move data between regions without your written consent.
The voice prompts explicitly instruct the model to write native Thai a Thai customer would actually type and read — not translated-feeling Thai. English copy tells the same product story but is not a literal back-translation. We strongly recommend your category lead spot-checks the first hundred outputs and we tune voice prompts based on the edits — that pass usually closes the residual machine-translation feel.
The four built-in voices ship locked in the demo. Tenant-specific voice tuning is part of pilot scope, not the public open demo — we sit with your brand lead, capture the voice rules, and build a fifth (or sixth, or tenth) voice profile inside your tenant. Voice editing through a UI is on the roadmap; right now it's a configuration step we run with you.
The voice prompt explicitly tells the model never to invent specs, certifications, awards, or claims that are not in the input data. Missing facts are worked around — if the supplier sheet does not list wattage, the copy never mentions wattage. This is baseline behavior, not a separate guardrail layer; it depends on prompt discipline, which is why every output should still be reviewed by a human before it ships, especially for regulated categories like food, pharma, and electronics.
No. CatalogAI calls a hosted AI vision/language model for every generation. The model and your retailer environment both need an internet connection at the moment of generation. Once the JSON has been generated, the result is yours to store, edit, export, and ship offline — but the generation step is online by design.
CatalogAI is built by Inline One Systems, a Bangkok-based product studio. Our founder previously built and shipped customer-facing platforms across Southeast Asia between 2017 and 2026 — including production systems with bilingual content, marketplace integrations, and Thai-language UX delivered for retail and consumer-facing operators. CatalogAI carries that operational pattern forward into a focused tool for Thai catalog teams.
A 30-minute walk-through. Bring one of your recent supplier sheets — paste it, drop the CSV row, or upload the PDF. We'll generate the bilingual listing in your store-brand voice live, and review the keyword pass with your category lead. If the shape fits, we scope a structured engagement at one category line. If it doesn't, you leave with a clearer view of what your catalog operation actually needs.