Trusted Enrichment: AI product data enrichment
you can check

Trusted Enrichment is how SKULaunch enriches product data with AI and shows its working. Every proposed attribute value links to the source it came from, the evidence on that source, how it was read and the decision a reviewer made. When sources disagree you see both. Nothing is published blind.

The SKULaunch Trust Graph behind one attribute value: source, evidence, reasoning and decision linked to a 70 Nm torque value

Why a filled field isn't a verified fact

A catalogue can be 98% complete and still be wrong in the places that matter. Most AI enrichment tools return tidy, confident tables with no trail behind them. You cannot tell which values were read from a datasheet, which were copied from an older version of the product and which were simply likely. So teams either recheck everything by hand, or publish errors to every channel, where marketplaces and AI shopping assistants repeat them.

How the SKULaunch Trust Graph works

Every value Trusted Enrichment proposes is recorded in the SKULaunch Trust Graph, so you can trace any attribute back to where it came from and why it was accepted.

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Source

Your rules decide which sources are trusted. Rank your approved data, supplier files, manufacturer documents, trusted domains and the open web, by category or by attribute.

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Evidence

The passage, table or image region on the source is kept with the value, with the date it was found.

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Value and reasoning

How the product was matched, which attribute the value maps to and any conversion applied. Stated and inferred values are labelled differently.

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Decision

Accept, edit or reject. Every decision records who made it and when.

What happens when sources disagree

Take the DeWalt DCD796 cordless drill. Current listings give a maximum torque of 70 Nm. An older datasheet for the same model code gives 60 Nm. Trusted Enrichment keeps both. The 70 Nm value is proposed because it is tied to evidence for the current version, from a source your rules rank higher. The 60 Nm value stays on the record as conflicting evidence. Any SKU that cannot be confidently matched to the current version goes to review instead of going live.

Two sources disagree, 70 Nm and 60 Nm; 70 Nm is proposed for the current version and 60 Nm is kept as evidence

Built for technical catalogues

Trusted Enrichment is designed for catalogues where one wrong specification costs a return, a failed compliance check or a broken filter.

Blue check mark symbol indicating completion or approval.
Products matched on brand and manufacturer part number before any value is proposed
Blue check mark symbol indicating completion or approval.
Units and formats normalised to your rules, so 18V, 18 volts and 18 V become one value
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Values constrained to your taxonomy, attribute definitions and permitted values
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Strong in electrical, industrial, automotive, tools and building supplies
Product matched on brand and part number, and 18V, 18 volts and 18-volt normalised to one permitted 18 V value

Review where the risk is

Nobody has time to check 20,000 values one by one. Trusted Enrichment sends the straightforward, well-sourced values through and puts your team's attention on conflicts, inferred values and the attributes you mark as critical. Every value can still be audited later, because its evidence travels with it.

Review queue sorted by risk, with conflicts, inferred values and critical attributes at the top

How Trusted Enrichment differs from a general AI tool

General AI tool SKULaunch Trusted Enrichment
Source shown for each value Rarely Always, with the evidence
Product match check Best guess Brand and part number matched, uncertain matches reviewed
Conflicting sources One value picked, the other lost Both kept, settled by your rules
Fits your taxonomy and units Only if prompted each time Built in
Review trail None Who decided, and when
Sync to PIM and channels Copy and paste Push to Akeneo, Shopify, Plytix, Magento and Mirakl

Related capabilities

Enrichment Studio

Where Trusted Enrichment runs

Explore →

Product data quality

Rules and checks across the catalogue

Explore →

AI product data extraction

Read supplier PDFs and spreadsheets

Explore →

Product data enrichment

The full guide to enrichment

Explore →

Frequently asked questions

What is Trusted Enrichment?

Trusted Enrichment is SKULaunch's AI product data enrichment that records the source and evidence behind every attribute value. Each proposed value carries its source, the evidence from that source, how it was derived and the review decision, so your team can check any value before it is published.

What is the SKULaunch Trust Graph?

The SKULaunch Trust Graph is the record behind each value: the source, the evidence, the value and its reasoning, and the decision. It is what lets you trace any attribute back to where it came from.

Can I control which sources SKULaunch trusts?

Yes. Source priority is configurable, so you can rank your own approved data, supplier files, manufacturer documents, trusted domains and the open web, and set different rules by category or attribute.

What happens when two sources give different values?

Both values are kept with their evidence. Your source rules decide which is proposed, and anything the rules cannot settle is flagged for review rather than averaged or guessed.

How is this different from using ChatGPT?

A general AI tool returns a value without a traceable source, product match check or review trail. Trusted Enrichment ties every value to evidence, applies your taxonomy and source rules, and records who accepted it.

How can I try it?

Start a free one month trial on up to 1,000 of your own products. No card is needed.

Try it on 1,000 of your own SKUs

One month free, up to 1,000 products across up to three categories, no card needed. Upload your messiest supplier file and check the source behind every value.

© 2026 SKULaunch Ltd. All rights reserved.
Built for e-commerce teams who are done doing it by hand.