Deduplication
The definition as the field writes it comes first, weaknesses and all. What Entity Bind does about it comes last, in its own paragraph, so you can take one without the other. Filed under foundations.
What the problem is called, and what the objects in it are. Entity, record, cluster, and the four industry names for the same job.
every figure, with its population →What deduplication means
Deduplication is the case where the file is compared against itself. A CRM with four rows for the same customer, a supplier master with three vendor codes for the same legal entity, a marketing list assembled from six imports — all of them are the same problem, and all of them have the same trap, which is that collapsing is destructive and finding is not.
Separate the two halves. Finding duplicates is a retrieval and scoring problem with a tolerable error profile: a false candidate costs a reviewer a few seconds. Merging duplicates is a write, and a wrong merge is expensive to detect and often impossible to reverse cleanly once downstream systems have replicated the surviving id. Most deduplication disasters are not detection failures; they are detection successes that were applied automatically at a threshold nobody measured.
The two failure modes have names. Merging records that are not the same company is an over-merge; leaving records that are the same company in separate clusters is fragmentation. They trade off against each other, and any single-number 'match rate' hides which one a tool prefers.
Entity Bind makes the merge a decision with a receipt, refuses any binding below the 0.90 confidence floor, and writes nothing into your systems: a Merge Safety Sprint returns which rows are the same company, which of your existing matches it would not have made, and what it could not decide. It is an acceptance contract, not calibration evidence: it says what we refuse to return, not how often an accepted match is right. Read it with the coverage it costs.
Where this shows up in Entity Bind
Three pages where this term stops being vocabulary and starts changing an answer, a payload or a price.
- What is entity resolution?Entity resolution decides which records in one or more datasets refer to the same real-world entity, and joins them under a single stable identifier.Open
- CRM and RevOpsThe duplicate-account problem in a running CRM, and what a merge that should not have happened costs to unwind.Open
- Compared with fuzzy matchingA score for how alike two names look, against a decision about which company they name — and the rows where the fuzzy matching you already run wins.Open
The fastest way past a definition is a file: which of your rows are the same company, which of your existing matches we would not have made, and what we could not decide.
Start freeThe terms next to this one
Each with its own sentence, because the next question is usually about the word beside this one.
Entity resolution
Entity resolution is the process of deciding which records, across one or many datasets, refer to the same real-world thing — and, when the evidence does not settle it, deciding that too.
Over-merge
An over-merge is a cluster containing records from more than one real entity — the failure that turns two customers, two suppliers or two counterparties into one.
Fragmentation
Fragmentation is the opposite failure to over-merging: one real entity split across several clusters, so the same company is counted, contracted with or invoiced more than once.
Golden record
A golden record is the single assembled view of an entity built by choosing one value per field from the records attached to it, ideally with the provenance of each choice carried alongside it.
Confidence floor
A confidence floor is the score below which a system refuses to return a match at all, expressed as an acceptance contract rather than as a promise about accuracy.
Decision receipt
A decision receipt is the durable, retrievable record of why a particular match was made — the features, the probability, the thresholds in force, the sources cited and the version of the pipeline that decided — addressable by an identifier returned with the answer.
- GuideHow to deduplicate a CRMExport, preview, tier the file, run it, review the abstentions, merge with receipts, measure. The full sequence for deduplicating a CRM account object without making a wrong merge you cannot undo.
- GuideHow to deduplicate a supplier masterDuplicate vendors, payment leakage, remittance conflicts and parent concentration. The accounts payable playbook for finding which vendor records are one company, with a citation for every finding.
- IntegrationSalesforceAn integration pattern, not a managed package: a named credential, a callout that resolves an account, and fields for the receipt. Nothing is written back.
- GuideEntity resolution vs record linkage: which term is rightRecord linkage, entity resolution, deduplication, entity matching, entity linking and identity resolution name overlapping problems from different fields. What each term means and when each one is correct.
The other 9 terms on this shelf
What the problem is called, and what the objects in it are. Entity, record, cluster, and the four industry names for the same job.
Internal fixtures only. The historical 2026-08-29 per-tier recording covers 317 GB companies with identifier-rich arrivals seeding the catalogue first; the context tier includes country and registered-town prose. Its legacy replay has no full-prompt-verified calls and cannot certify current calibration. The September 5 CI reports cover 1,176 labelled pairs and 705 records over 250 companies using offline stubs. These are not independent customer holdouts or live production validation; the 99% minimum-input product target remains unmet. Scope is company and organisation identity only — not people, vessels, bank-account ownership, sanctions or emissions. Results may not be used for eligibility decisions about individuals, including employment, credit and tenancy.
Start with your own company records.
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For a guided review of your file, explore the Merge Safety Sprint →