{"uid":"cap_lopBI-fdLnjYHD_AXHSG-","slug":"entity-resolve-fuzzy-record-deduplication-e1877e81","name":"Entity Resolve – Fuzzy Record Deduplication","description":"Fuzzy-dedupe a list of records into clusters of likely-duplicate entities. Blocks by normalized token prefix, scores with Jaro-Winkler + token-set matching (exact on email/phone), unions matches above threshold, and returns a merged canonical record per cluster with a confidence score. Deterministic, no LLM calls.","url":"https://entity-resolve.x402supply.com/tools/resolve?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"options":{"type":"object","properties":{"keys":{"type":"array","items":{"type":"string"},"minItems":1},"threshold":{"type":"number","default":0.82,"maximum":1,"minimum":0}},"additionalProperties":false},"records":{"type":"array","items":{},"maxItems":10000,"minItems":1}}},"responseSchema":{"type":"json","example":{"skipped":[],"clusters":[{"members":[0,1],"canonical":{"name":"ACME Corporation","email":"info@acme.com"},"confidence":0.971},{"members":[2],"canonical":{"name":"Globex LLC","email":"hello@globex.com"},"confidence":1}]}},"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.02","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"probe","requiresHandshake":false,"reviewCount":0,"rating":{"score":"0.00","successRate":"0.00","reviews":0,"stars":null,"state":"unrated"},"availabilityStatus":"unknown","priceObserved":null,"sessionDeposit":null,"pricing":{"kind":"static","summary":"$0.02/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.02","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.02","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_m_BcPK8swfc4kRvDL_sJP","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.02","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Fuzzy-deduplicates a list of records into clusters of likely-duplicate entities, returning a merged canonical record per cluster with a confidence score","exampleAgentPrompt":"I have a list of 500 customer records that probably have duplicates — can you run fuzzy deduplication on them using name and email as the matching keys, with a similarity threshold of 0.85, and give me back one canonical record per cluster with a confidence score?","exampleUseCases":[{"title":"CRM duplicate contact cleanup","prompt":"I exported our CRM and there are clearly duplicate contacts — same person with slightly different name spellings or email formats. Can you cluster them by name and email fields with a 0.85 threshold and give me the merged canonical record for each duplicate group?"},{"title":"Vendor list deduplication","prompt":"We have a procurement spreadsheet with about 2,000 vendor entries and a lot of duplicates — different abbreviations, typos, same company listed multiple ways. Can you fuzzy-match them by company_name and phone, merge the duplicates, and tell me the confidence score for each cluster?"},{"title":"Event attendee list deduplication","prompt":"We collected attendee registrations from three different forms and there's overlap. Can you deduplicate these records by matching on first_name, last_name, and email with a threshold of 0.82 and return one canonical entry per person?"}],"resultDescription":"Returns clusters of records determined to be likely duplicates, each cluster containing a merged canonical record that combines the best-available field values from the grouped records, along with a confidence score indicating how certain the match is. Uses Jaro-Winkler and token-set similarity with exact matching on email and phone fields.","failureModes":["Empty records array returns validation error","Threshold outside 0–1 range rejected","Records array exceeding 10,000 items rejected","Malformed record objects may produce low-quality clusters","Missing keys field may result in all-field comparison or error","Payment failure returns 402 status"],"whenToPreferThis":"Choose this endpoint when you need deterministic, reproducible entity resolution without LLM calls — ideal for compliance-sensitive pipelines, high-volume batch deduplication, or when you need explainable similarity scores. Prefer it over LLM-based matching when consistency and cost predictability matter, and over simple exact-match deduplication when records have typos, abbreviations, or formatting inconsistencies.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-13T18:37:28.696Z","isFirstParty":false,"canonicalSlug":"entity-resolve-fuzzy-record-deduplication-e1877e81"}