"18V", "18 Volts",
"18v".
Now they're all
the same thing.

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.

The Notes App for Power Users - Techbeta X Webflow Template
The Notes App for Power Users - Techbeta X Webflow Template
The Notes App for Power Users - Techbeta X Webflow Template
100%
Tasks completion rate
10M+
Capital raised

0

Manual mapping rules written

Any

Number of sources, one schema

100s

Value variants handled automatically
How it works

One schema. Any number of sources.

Three normalisation layers — unit standardisation, value mapping, and cross-source alignment — applied automatically every time data enters SKU Launch.

⚖️

Unit standardisation

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.

🔄

Value mapping

"Blue", "BLUE", "Royal Blue" — AI maps value variants to your accepted list. Works across colours, statuses, sizes, and any other controlled vocabulary.

🌐

Cross-source alignment

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.

UNIT STANDARDISATION

Every supplier uses different units. Now it doesn't matter.

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.

Weight: kg, g, lb, oz all normalised to your preferred unit
Voltage: V, Volts, volts, v all normalised to V
Dimensions: mm, cm, m, inches all converted and standardised
Power: W, Watts, kW all to your defined format
Custom unit rules — define your own standard for any attribute
VALUE MAPPING

Controlled vocabularies that actually get controlled.

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.

Maps to accepted values without supplier re-submission
Handles capitalisation, spacing, and abbreviation variants
Colour mapping — "Navy", "Dark Blue", "Midnight Blue" → "Blue"
Size mapping — "L", "Large", "LG" → "L"
Low-confidence mappings flagged for human review
CROSS-SOURCE ALIGNMENT

Every supplier names their columns differently. AI doesn't care.

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.

Semantic field name matching across all sources
Handles abbreviations, synonyms, and language variants
Works across supplier portals, spreadsheets, and data feeds
Confidence score per mapping — review queue for edge cases
also in DATA STRUCTURE

Explore the full platform

Data Structure is one of three pillars.

DATA STRUCTURE

Schema & Attributes

Define what to normalise to - and AI builds your schema in minutes.

Explore →
DATA STRUCTURE

Mapping & Normalisation

You're here.

DATA STRUCTURE

Product Data Quality

After normalisation, quality scoring tells you what's ready to publish.

Explore →
SOURCE ONBOARDING

Imports & Spreadsheets

Normalisation kicks in the moment a spreadsheet is uploaded - messy columns map automatically.

Explore →
ENRICHMENT & CONTENT

Content Generation

Normalised attribute values produce more accurate, consistent product descriptions.

Explore →

Build your first schema in the demo

Book 30 minutes. We'll generate a schema for your product categories live — and show you how it connects to onboarding and enrichment.

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Built for e-commerce teams who are done doing it by hand.