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entity-resolve
x402
entity-resolve is a paid API for AI agents from entity-resolve.x402supply.com, paid per call via x402, $0.02/call, status unknown (last checked 2026-09-15).
Fuzzy-deduplicates a list of records into clusters of likely-duplicate entities, returning a merged canonical record per cluster with a confidence score.
Price / call$0.02
Success—
StatusUnknown
How this service works
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.
Output
A list of entity clusters, each containing the matched records grouped together, a merged canonical record synthesizing the best available field values, and a confidence score (0–1) indicating how certain the algorithm is that the records refer to the same entity. No LLM inference is involved — results are deterministic based on Jaro-Winkler + token-set scoring and union-find clustering above a configurable threshold.
Example use cases
CRM deduplication before campaign launch
“I have a CSV export of 2,000 leads from our CRM with a lot of duplicates — same person with slightly different name spellings or email variations. Can you run it through entity resolution and give me the deduplicated canonical list with confidence scores so I know which merges to trust?”
Merging vendor lists from two acquisitions
“We just merged two companies and both had separate vendor databases. Can you take both lists, fuzzy-match them by company name and phone number, and cluster the ones that are clearly the same vendor so we can eliminate the duplicates?”
Cleaning scraped business directory data
“I scraped business listings from a few different directories and there are tons of duplicate entries with slightly different names or addresses. Can you cluster these into groups of likely-same businesses and return one canonical record per business along with how confident you are in each merge?”
Technical details
Endpoint
POSThttps://entity-resolve.x402supply.com/mcpWhen to prefer
Choose this endpoint when you need deterministic, auditable entity deduplication without LLM involvement — especially when reproducibility matters and you can't risk non-deterministic AI output. Ideal for cleaning CRM exports, merging data from multiple sources, or preprocessing datasets before analytics. Prefer this over LLM-based matching when you need consistent results across repeated runs or when cost predictability is important at $0.02 per call.
Side effects
- Records with no overlapping tokens may not be blocked together and will be missed
- Very short or ambiguous names may produce false positives or false negatives
- Missing email/phone fields reduce match precision since those fields get exact matching
- Threshold misconfiguration can cause over-merging or under-merging of clusters
- Malformed input records (missing required fields) may cause processing errors
- Extremely large record lists may exceed per-call size limits
Tags
x402
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