Curious how product enrichment runs on your data? We'll show you on one real file.
See it on your data →Enrichment is only worth it if the values hold up
An incomplete product page costs conversion twice — once when a shopper cannot find the spec they need, and again when the product is silently excluded from a filter it should have matched. Manual enrichment cannot keep pace with thousands of SKUs across dozens of suppliers, and generic AI enrichment solves the speed problem by inventing values that are almost right — which, on a spec sheet, is the same as wrong. Claro only fills a field when a source document supports it, and records exactly where the value came from, so an enriched record is something your team can stand behind, not just something that looks complete.
Why attribute gaps survive every cleanup project
Incomplete product pages hurt conversion and get products excluded from filters entirely.
Manual enrichment does not scale across thousands of SKUs and dozens of suppliers.
Generic AI enrichment invents attributes that are almost right, and almost right is wrong.
How product data enrichment works with Claro
What is missing across the record.
The value, from a document you already have.
Exactly where it came from, every time.
Only when the source supports it — never guessed.
Who needs enrichment with provenance
What goes in, what comes back
Claro writes back through files and APIs rather than certified connectors, so this list is a guide, not a limit.
Product enrichment: common questions
Where do the filled values come from?
From documents you already have or that Claro can cite — datasheets, manuals, certificates, manufacturer pages. A field is filled only when a source supports it.
Does Claro ever invent an attribute?
No. If no source supports a value, the field stays empty and is reported as a gap. A missing value is cheaper than a plausible wrong one, which is the failure mode of generic AI enrichment.
What happens when two sources disagree?
The conflict is surfaced rather than silently resolved. You see both values with their sources, and the record routes to review instead of picking a winner on your behalf.
How many attributes can it fill?
It depends on the category schema and the evidence available. In one engagement a record went from 7 attributes in the raw ERP export to 32 technical specifications, every one carrying a source and a confidence score.
Does it work on non-English documents?
Yes. Italian, German, French and other source documents are read in their own language, and the extracted values are normalised into your schema and units.
Related work
See it work on your own catalog.
Bring one supplier file and we'll run product enrichment on your real data — matched, classified and reviewable.