ENRIVAQ — AI product data enrichment
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Process VeilGroup 02 · one product moving through evidence
03 phasesidentify · structure · prepare
09 stagesone ordered workflow
01 productsame SKU through every state
How product data enrichment works

From Incomplete SKU to Validated Product Record

Product-data enrichment starts with the information you already have and builds from there.

ENRIVAQ takes a product through identification, research, technical extraction, normalization and validation, then builds SEO keyword targets, unique factual content, SEO metadata and target-language output before the finished card returns to your catalog workflow.

Process a Sample CatalogSee the real example
01
Import
02
Identify
03
Sources
04
Extract
05
Normalize
06
Validate
07
SEO + Content
08
Review
09
Export
Chapter
01
Identify the product

Start with what you have. First prove what the product actually is.

The first three steps establish a reliable identity and usable evidence base before any technical values are accepted.

01
Import

Start with the product data you already have

The initial record is deliberately incomplete. Missing data remains visible without turning normal supplier input into an error state.

The existing record becomes the starting point for enrichment.
SKU
EAN 8716106986118
Manufacturer
KVERNELAND
OEM / MPN
AC820825
Supplier title
FAN IMPELLER AC820825
Existing attributes
Limited supplier fields
Description
Not provided
Raw state
Incomplete by design

Enough information to begin identification. Not yet enough for a dependable technical product record.

SKUOEMTITLEATTRIBUTES
02
Identification

Confirm the product before researching it

Identifiers and product context converge on one record. Research begins only after the product match is established.

High-quality information about the wrong product is still wrong product data.
SKUEAN 8716106986118
ManufacturerKVERNELAND
OEM numberAC820825
Title signalFAN IMPELLER
Product matched

AC820825

IDENTITY CONFIRMED FOR RESEARCH

Why this stage existsThe system should not search broadly for “a similar fan.” It should establish which exact product record the available identifiers describe.
03
Source discovery

Find evidence relevant to the matched product

Sources are shown by approved category, without invented domains or unsupported claims.

Sources become evidence for structured extraction and validation, not decoration around an AI answer.
Source A

Manufacturer source

Product context and technical reference.

● relevant
Source B

Technical documentation

Specification evidence available for extraction.

● relevant
Source C

Distributor source

Comparable product values requiring comparison.

● compare / review
Chapter
02
Structure & trust

Turn evidence into catalog data — then challenge it before accepting it.

Extraction makes information usable. Normalization makes it consistent. Validation decides what can safely move forward.

04
Extraction

Convert source statements into catalog fields

Source language stays visible beside the structured result, so the transformation can be understood and checked.

Structured output makes the information usable in PIM, ecommerce filters and downstream workflows.
Raw source
“Kverneland AC820825 fan wheel for Optima / Optima HD …”
RAW SOURCE → STRUCTURED DATA
Structured record
AttributeOEM / MPN
ValueAC820825
AttributeCompatibility
ValueOptima / Optima HD
05
Normalization

Resolve different formats into one canonical value

Normalization is presented as a data-quality operation, not content generation.

The goal is a catalog where similar products follow the same data rules.
FieldAs foundCanonicalStatus
Product typeFan wheel · GebläseradFan impellerAccepted
Manufacturer referenceOEM · MPN · part no.AC820825Accepted
Weight1.74 kg · 2.60 kgConflict → ReviewReview
CompatibilityOptima · Optima HDOptima / Optima HDAccepted
06
Validation

Check before accepting the result

Matching evidence can continue. Conflicting or incomplete values keep their context and move to review.

Records requiring a decision can move into review instead of being silently accepted.
Validation checkpoint

Make problems visible before publication

Matching values are accepted. Conflicts and missing evidence remain visible.

Evidence before acceptance
Product matchidentity established before researchPassed
Schema checkcatalog field and unit verifiedPassed
Cross-source checkconflict or missing evidenceReview
Chapter
03
Prepare for use

Build the full product card from facts, route exceptions to people, return the approved result.

Once the product record is structured and validated, the workflow identifies relevant SEO search terms and produces the unique product title, description, SEO metadata and target-language output required for the final card.

07
Content

Build SEO and content from accepted product facts

Validated technical data becomes the factual base. SEO keyword targets then guide unique copy and metadata without introducing unsupported specifications.

The order matters:
validated facts → SEO terms → copy + metadata → target language.

Accepted product facts

OEM / MPNAC820825
EAN8716106986118
Product typeFan impeller
CompatibilityOptima / Optima HD
WeightReview · excluded from copy
Product titleSEO keywordsDescriptionSEO metadataLanguage
Kverneland AC820825 Fan Impeller for Optima Planters
Technical attributes stay structured; the same accepted facts drive the SEO keyword set, unique product copy, meta title, meta description and localized final card.
● structured input● validation context retained
08
Review

People handle exceptions, not repetitive research

The branch is explicit: routine accepted records continue; uncertain records arrive with evidence for a decision.

A reviewer sees product data, supporting sources and relevant context rather than checking the result blindly.
Routine path

Continue automatically

Records that satisfy the agreed rules continue through the normal workflow.

  • matched context
  • normalized format
  • accepted values
DECISION
Exception path

Human review

Humans focus on cases where context or judgment is genuinely useful.

  • conflicting values
  • missing required fields
  • uncertain evidence
09
Export

Return the approved record to the existing workflow

The diagram stays generic until exact production methods are verified.

Only implemented production methods should be presented as supported.
Approved output
Structured attributesready
SEO keyword setready
Unique product contentready
SEO metadataready
Target-language outputready
Review-required fieldsheld back
Connected catalog
ERP-related workflow
Ecommerce
Configured site export
API input
One record · complete history

Audit the same product through every stage

Follow the same agricultural spare-part record from incomplete input to an approved record ready for hand-off.

Before · input

OEM / MPNAC820825
Supplier titleFAN IMPELLER AC820825
Descriptionnot provided
Technical structurelimited
Sourcesnot attached
same SKU

After · approved record

Identityconfirmed
Sourcesattached to record
Attributesstructured + normalized
Validationaccepted / review states visible
SEO + contentkeywords · unique copy · metadata · target language

Try the workflow on a representative product

Send a sample SKU or catalog extract and see how the process applies to your product data.

Process a Sample Catalog

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