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Solutions / Catalog AssemblyWorkload weave · routine compression
Manual product data enrichment
Replace Repetitive Catalog Research with an AI Workflow
Manual product data enrichment works because experienced people know how to search, compare and interpret product information.
For ENRIVAQ, enrichment means completing the usable card: validated technical attributes are combined with SEO keyword targets, unique factual product content, SEO metadata and target-language output rather than being delivered as attributes alone.
The problem is that the same routine has to be repeated for every new or incomplete SKU. ENRIVAQ is designed to automate the repetitive part of that work: identifying the product, researching relevant sources, extracting structured attributes and validating the result before it enters the catalog.
People remain in the workflow where judgment is needed. The goal is not to remove expertise. It is to stop spending expert time on the same search-and-copy process thousands of times.
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Reasonable once
bottleneck when repeated
bottleneck when repeated
Catalog batchDefined enrichment pipelineStructured output
IdentifyProduct contextResearchRelevant sourcesStructureFields and unitsValidateControlled result
Exception tray · uncertain matches, conflicts and unsupported critical fields remain for human judgment.
Manual workflow
The manual process is simple — and expensive to repeat
A catalog specialist usually starts with a product number, short title and a few supplier fields, then builds the record through a sequence of reasonable individual actions.
01Search for the correct product and manufacturer reference.Manual
02Open and compare several candidate sources.Manual
03Find the specifications that matter for the category.Manual
04Interpret supplier terminology and units.Manual
05Copy data into the target catalog structure.Manual
06Write or improve product content.Manual
07Check the record before publication.Manual
Bottlenecks
Repeating the loop for every SKU creates the bottleneck
The process also becomes inconsistent. Two employees may choose different sources, name the same attribute differently or apply different rules when information conflicts.
Research time
The same types of information are researched again and again.
Different choices
Employees or suppliers use different attribute names and units.
Lost context
Quality control becomes difficult when source context is not retained.
Growing backlog
New products arrive faster than the catalog team can enrich them.
Automated workflow
Turn the repeated manual sequence into a defined enrichment workflow
The product can start with the same incomplete record, but research, extraction, normalization and validation become explicit stages rather than ad-hoc browser work.
AC820825Incomplete record
Next supplier recordSupplier input
Record with open gapsOpen gaps
Record with mixed fieldsMixed fields
Defined
route
route
01 · ImportAvailable record
02 · IdentifyIdentifiers + context
03 · ResearchRelevant sources
04 · ExtractStructured attributes
05 · NormalizeTerminology + units
06 · ValidateConflicts + uncertainty
07 · ReviewExceptions only
08 · ExportApproved result
The output remains structured so it can return to a PIM, ecommerce platform or another downstream process.
Human role
Let people handle exceptions instead of routine research
Automation should not turn technical catalog management into blind acceptance of AI output. Human expertise is most valuable where judgment is genuinely required.
Clear product identityContinue
Relevant source foundContinue
Supported structured fieldContinue
Approved normalizationContinue
Route by
evidence
evidence
Uncertain identificationHuman review
Conflicting technical valuesInvestigate
Unsupported critical fieldLeave unresolved
Interpretation requiredReviewer decision
Cost model
Measure the current process before calculating automation value
The cost of manual enrichment is often hidden inside catalog, ecommerce or product-management work.
Compare the measured baseline with the automated workflow plus the human review that remains.
Catalog sizeEnter your catalog size
Average manual minutes per SKUMeasure the current workflow
Internal hourly costUse your internal labor rate
Estimated automation coverageMeasure after the pilot
Remaining review timeMeasure on the exception set
Quality
Automation should make the process more controlled, not less
A faster workflow is useful only if the catalog remains technically reliable. Repetitive work can be automated without treating every generated value as true by default.
Source contextEvidence stays connected where implemented.
Structured fieldsOutputs follow the target schema.
NormalizationApproved terminology and units.
ValidationConflicts and uncertainty remain visible.
Human reviewUncertain cases keep a person in the loop.
Start with the products your team spends the most time researching
Choose a representative set of difficult SKUs and compare the current manual workflow with the enrichment process.