Tag it, annotate it, localise it.
Product models are only as good as the labels behind them, and a marketplace that serves India is only as good as its Hindi, Tamil and Bengali. We tag attributes, annotate images and localise catalog and support content with trained annotators and native-language reviewers. AI drafts and pre-labels at volume, available as a pilot. People set the gold standard, resolve the ambiguous cases and sign off what ships.
Labels a product model can learn from.
Manual tagging and annotation is patient, exact work. Our annotators label product attributes, draw and class bounding boxes and place products in your taxonomy, working to written guidelines and measured against gold sets. It is the same discipline we apply on our annotation platform for autonomous-vehicle map data, brought to catalog imagery. The service sits in our marketplace operations group.
- Attribute labellingColour, material, pattern, sleeve, fit, occasion and the rest of your schema, tagged per SKU from images and text, with the source of each value recorded.
- Image annotationBounding boxes, polygons and classes on product photos: the product, the model, logos, defects and packaging, drawn to your specification.
- Taxonomy labelsEach product placed in your category tree, with the ambiguous cases (a card holder or a wallet, a tunic or a kurta) escalated to a lead annotator rather than guessed.
- Gold sets and inter-annotator agreementA reviewed gold set anchors every batch. Agreement between annotators is measured, and batches below the band you set are re-worked before release.
- AI pre-labelling, available as a pilotModels draft the easy labels first. Annotators correct and confirm, and every correction feeds back into the guidelines.
| Item | Tags | Boxes | Agreement | Status | |
|---|---|---|---|---|---|
| Linen midi dress | 14/14 | 2 | 0.94 | released |
| Black crew-neck tee | 11/11 | 3 | 0.91 | released |
| Bifold leather wallet | 7/9 | 1 | 0.62 | held |
| True wireless earbuds | 9/9 | 2 | 0.96 | released |
 | Two-tone leather tote | 12/12 | 2 | 0.78 | re-work |
Titles, descriptions and support in the buyer’s language.
A Hindi title that reads like a translation loses the buyer. We localise catalog content and support into Indian languages with an AI draft, available as a pilot, and a native reviewer who owns the final text. The same reviewers sit behind regional-language helpdesk scripts. For catalogs that already exist in several languages and need checking, see multilingual catalog QC.
- Vernacular catalog contentTitles, bullets and descriptions written for Hindi, Tamil, Bengali and other regional markets, keeping the attributes exact and the tone local.
- AI draft, native reviewerThe model produces the first draft and a glossary check. A native-speaking reviewer edits, approves and signs. Nothing publishes on the draft alone.
- Regional-language supportHelpdesk scripts, macros and knowledge articles localised so buyers and sellers get help in their own language. See buyer and seller helpdesk.
- Glossary and brand terms heldProduct names, units and brand terms are locked in a glossary per language so they do not drift between SKUs or between reviewers.
Read the catalog the way a buyer reads it.
Beyond the schema check, we read titles and descriptions for meaning: does the text say what the product is, in the right language, without the errors a native speaker would notice. AI reads at volume, available as a pilot. Reviewers decide what is a fault and what is a style choice.
Language and script detection
Confirms each field is in the language it claims to be, and flags mixed-script or machine-mangled text before a buyer sees it.
Grammar and readability
Sentence-level checks for grammar, spelling and readability in each language, tuned to marketplace copy rather than to prose.
Attribute consistency
Title, bullets and description are cross-read so the colour, size and material agree with each other and with the structured fields.
Prohibited and risky claims
Health, safety and comparative claims are flagged for a reviewer, along with any term your policy does not allow in a listing.
Glossary and brand adherence
Brand names, product terms and units are checked against the per-language glossary, so the same product is called the same thing everywhere.
Reviewer disposition on record
Every flag is closed by a named reviewer with a disposition (fixed, accepted or escalated), so the same issue is not re-argued in the next batch.
Let’s build smarter, faster and more scalable e-commerce experiences together.
Explore how AI + creativity can accelerate your next big move. Bring one category and one language. Leave with a labelled sample, the agreement score behind it and a localised set your native reviewers have signed.