AI agents standardise units, field names, and values across every data source — automatically. No VLOOKUP. No manual mapping rules. No spreadsheet gymnastics. One schema, however many suppliers.
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Three normalisation layers — unit standardisation, value mapping, and cross-source alignment — applied automatically every time data enters SKU Launch.
AI converts all variants of a unit to your standard format. "1.5 kg", "1500g", "1.5 kilograms" all become "1.5kg" — whatever your schema defines as canonical.
"Blue", "BLUE", "Royal Blue" — AI maps value variants to your accepted list. Works across colours, statuses, sizes, and any other controlled vocabulary.
Field names vary by supplier — "input voltage", "operating voltage", "battery voltage" all mean the same thing. AI detects intent and maps to the right schema attribute.
Units are the most common source of dirty product data. One supplier writes "1.5 kg", another writes "1500g", a third writes "1.5 kilograms." AI normalises all of them to your defined standard — every time, across every source, without a rule being written.





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You define the accepted values for each attribute. AI maps every incoming variant to the right one — even when suppliers use their own naming conventions, abbreviations, or slightly different spellings. No rejected submissions, no cleaning work afterwards.





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Supplier A calls it "input voltage." Supplier B calls it "operating voltage." Your ETIM feed calls it "nominal voltage." AI detects that all three mean the same thing and maps them to the same schema attribute — without you writing a single rule.




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Data Structure is one of three pillars.
Book 30 minutes. We'll generate a schema for your product categories live — and show you how it connects to onboarding and enrichment.