ENRIVAQ — AI product data enrichment
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Product familysoft signal · controlled dataP4validationDecision fieldvalidation matrix8 scenescandidate → decision
Product data validation

Validate Product Data Before It Reaches Your Catalog

Generating product information is easy. Deciding whether it should be trusted is harder.

ENRIVAQ treats product data validation as a separate stage of the enrichment workflow so incomplete, conflicting or uncertain information can be identified before it is exported or published.

See Validation in ActionView conflict decision
VALIDATION FIELDBEFORE EXPORT · ILLUSTRATIVE STATES
Reference product AC820825
REFERENCE RECORDAC820825values to come from a verified record
CANDIDATE DATA

Materialschema · source · format checks

ACCEPTED

Lengthcandidate requires verified value

REVIEW

Widthavailable sources may disagree

CONFLICT

Bore diameterunit context required

REVIEW

Compatible applicationrequired field may be missing

HOLD
CANDIDATEVALIDATION LAYERSACCEPT / REVIEW / HOLD
Why validation

AI should help complete product data — not guess it

AI can extract and organize information from complex sources. But technical data creates several risks:

RISK SIGNALWHAT CAN GO WRONGDECISION CONTROL
01a source can refer to the wrong productproduct identity check
02multiple sources can disagreeconflict remains visible
03an attribute can be mapped incorrectlyschema and meaning check
04a unit can be misunderstoodformat and unit check
05a required specification can still be missingcompleteness check

A fluent AI response does not prove that the underlying value is correct.

The workflow therefore separates generation from acceptance.
Validation types

Check the product record from several angles

The approved architecture identifies five main areas.

LAYERQUESTIONEVIDENCE NEEDEDOUTCOME
01 · SchemaDoes the data fit the expected product structure?

target field · value type · required state

PASS / REVIEW
02 · SourceIs there relevant source context behind the value?

source statement · product match

PASS / HOLD
03 · FormatIs the value represented correctly?

format · unit · controlled term

PASS / REVIEW
04 · ConflictDo available sources disagree?

same field · comparable evidence

REVIEW / HOLD
05 · CompletenessAre required product fields still missing?

required field set · candidate record

PASS / HOLD
Together, these checks help determine whether a record can continue automatically or requires review.
Confidence

Confidence is a signal, not proof

Where confidence scoring exists in the implemented product, it can help prioritize what requires human attention.

ILLUSTRATIVE SIGNALNO PUBLISHED SCORE
Source evidenceNEEDS CONTEXT
Product identityCHECK MATCH
Extraction clarityCOMPARE EVIDENCE
Exact confidence model: Task-specific confidence signals are combined with source provenance, product identity, canonical mapping and conflict checks. Confidence is an operational signal, not a factual probability.
≠SIGNAL IS NOT PROOF
EVIDENCE BEHIND THE DECISION

A low-confidence value can indicate that

  • source evidence is weak
  • product identity is uncertain
  • extraction is ambiguous
  • available sources conflict

A high confidence value should not be presented as a guarantee of factual truth.

Conflict detection

Two credible sources can still disagree

Imagine two sources describing the same part number. Publishing one value automatically would hide a real uncertainty.

The validation workflow should surface the conflict so the system or reviewer can decide how the record should proceed.

CONFLICT DECISION ISLANDILLUSTRATIVE ONLY · NOT AC820825 DATA
SOURCE A · WIDTH1.74 kgillustrative candidate value
≠
SOURCE B · WIDTH2.60 kgillustrative candidate value
same product?same field?comparable source context?
CONFLICT SURFACED

Sent to validation, not published

REVIEW / HOLD
Human review

Use people where a decision is actually needed

The aim of validation is not to force every record into manual approval. It is to separate routine work from exceptions. A practical model is:

ROUTINE PATH

Clear / accepted

Evidence and structure support the candidate record.

continue
CANDIDATEROUTEDECISION
EXCEPTION

Uncertain

Evidence needs a human decision.

review
EXCEPTION

Invalid / conflicting

Do not hide the unresolved issue.

reject or investigate
Validation example

Show what the system rejected, not only what it accepted

Reference example: AC820825 public-source conflict.

REFERENCE VALIDATION RECORDPUBLIC SOURCE CONFLICT
Candidate valueWeight · 1.74 kg / 2.60 kg
Source ASELM Agro · 1.74 kg
Source BLBR · 2.60 kg
IssueConflicting source values
DecisionREVIEW / HOLD
Unresolved technical values remain outside the accepted record and generated content.

Showing rejected or uncertain data demonstrates control more convincingly than publishing only successful examples.

Next step

Test the workflow on a technically difficult product

Use a product with missing or conflicting specifications and see how the validation stage handles it.

See It on Your Data

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