What Is a Product Identity Graph?

A product identity graph turns one-off record matching into persistent identity knowledge: a canonical product linked to SKUs, MPNs, suppliers and documents with scored edges, including NOT_SAME_AS, that survive re-ingestion.

published product-identityknowledge-graphentity-resolution

A product identity graph links a canonical product to its identifiers, suppliers and documents with scored edges, including negative edges such as NOT_SAME_AS, that persist across ingestions. It turns one-off record matching into durable identity knowledge.

Matching two records is a moment. A product identity graph is the memory of every such moment: the canonical product and all the identifiers, suppliers and documents that resolve to it, kept so the next supplier feed does not start from zero.

Definition

A product identity graph links a canonical product to its identifiers, suppliers and documents with scored edges, including negative edges (NOT_SAME_AS), that persist across ingestions.

Most catalog tools match and move on. A supplier file comes in, a matching step decides which rows are duplicates, the catalog is cleaned and the reasoning evaporates. Next month the same file arrives and the same rows are matched again. A product identity graph is what you get when that reasoning is kept, written down as edges between a canonical product and everything that points at it.

SUPPLIER RECORDSRESOLVED IDENTITYRELATIONSHIPS & EVIDENCESupplier AAF16-30-10-13feed_a.csvSupplier BABB AF1630101013feed_b.xlsxSupplier CAF16-30-10-1124–60 V AC / 20–60 V DC coilNOT_SAME_ASCanonical productABB AF16-30-10-133-pole contactor · 100–250 V AC/DCMPN 1SBL177001R1310conf 0.98Datasheet1SBC101501D0205.pdfprovesp.3Coil voltage100–250 V AC/DChassrc datasheet p.3 · 0.98FamilyAF rangevariant_ofmanufacturer · 0.99Aux contactCAL4-11compatible_withcatalog · 0.95Write-backERP · PIM · ecommerce · agentssyncscontinuousmonitors & re-ingests
Fig. 1 — A canonical product, its supplier records and identifiers, the datasheet that proves a value, and the near-miss held as NOT_SAME_AS.

Record matching vs identity knowledge

Record matching Identity graph
Output A pairwise score A canonical entity with durable edges
Lifespan Today's run Persists across ingestions
New supplier feed Re-match from scratch New records attach to existing identities
Rejected pairs Discarded Stored as NOT_SAME_AS
Human review Repeated for the same pair Decided once, inherited afterwards

So ABB AF1630101013 from a new supplier lands on the existing AF16-30-10-13 identity automatically, not because it was re-matched, but because the graph already knows the two are the same.

Positive edges

Each edge carries a source and a confidence score.

  • SAME_AS: this record is the canonical product.
  • VARIANT_OF: a configuration of a parent (AF16 vs AF26).
  • SUPPLIED_BY: a commercial source and its SKU.
  • REPLACED_BY: the manufacturer’s successor part.
  • DOCUMENTED_BY: the datasheet or drawing that proves a value.

The full vocabulary and the lines between the easily confused ones are in the product relationship types guide.

Negative edges: the part most systems throw away

The graph also records what is not the product. AF16-30-10-11 is one digit away from AF16-30-10-13 but carries a 24–60 V AC / 20–60 V DC coil instead of a 100–250 V AC/DC one. A NOT_SAME_AS edge keeps that near-miss on file, so it is never silently merged in a later run and a reviewer never re-investigates a question that has been answered. Storing the rejection is the most valuable thing the graph does that a cleaned table cannot.

A minimal data model

ProductIdentity(id, canonical_name, manufacturer, mpn)
SourceRecord(id, supplier, sku, raw_text, source_file, observed_at)
Document(id, type, uri, page)

Edge(from, to, type, confidence, evidence_ref, decided_by, decided_at)
  type: SAME_AS | NOT_SAME_AS | VARIANT_OF | SUPPLIED_BY | REPLACED_BY | DOCUMENTED_BY

The details that make it work are on the edge: confidence routes the work, evidence_ref makes it defensible and decided_by records whether a rule or a person made the call.

Why it survives the next supplier feed

Because the edges are data and not a one-time computation, every ingestion inherits them. New records attach to existing identities, confirmed relationships raise confidence and only the genuinely new or ambiguous cases reach a human. That is the mechanism behind the claim that your catalog should get smarter every day: the identity graph is where “smarter” accumulates.

Common mistakes

  • Merging records and deleting the originals. Keep every source record linked, so a merge can be reversed.
  • Only storing positives. Without NOT_SAME_AS, near-misses return.
  • Edges without evidence. An unsourced SAME_AS is a guess with a nicer name.
  • Treating confidence as permanent. A supplier revision can change an edge; keep the timestamp.

Where Claro fits

A product identity graph is the identity-and-resolution core of the broader Product Identity & Evidence Graph. The entities it links are product identities, and the wider structure is described in product knowledge graph.

FAQ

What is a product identity graph?

A product identity graph links a canonical product to its identifiers, suppliers and documents with scored edges, including negative edges, that persist across supplier ingestions. It is the stored memory of identity decisions.

How is a product identity graph different from a product knowledge graph?

A product identity graph is the identity-and-resolution core: which records are the same product. A product knowledge graph is broader and also covers attributes, compatibility, classification and other relationships between products.

What is a NOT_SAME_AS edge?

A NOT_SAME_AS edge records that two products look alike but are different, such as two contactor variants that differ only in coil voltage. Keeping it stops the pair being merged in a later run and stops reviewers re-investigating it.

Does a product identity graph replace my PIM or ERP?

No. It sits alongside them. Your PIM and ERP remain systems of record, and the identity graph supplies the resolved identities and evidence that are written back to them.

Claro

See how Claro handles this in production

This concept is one piece of keeping a catalog trusted. See how Claro resolves identity, enriches missing attributes, and validates every update before it reaches your PIM or ERP.

Learn more