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Name Similarity Key Generator
x402
Name Similarity Key Generator is a paid API for AI agents from data.japanagent.dev, paid per call via x402, $0.001/call, status unknown (last checked 2026-10-11).
Generates a normalized phonetic fingerprint (similarity key) for a person or company name, enabling deduplication and entity resolution across datasets.
Price / call$0.001
Success—
StatusUnknown
How this service works
Generate a similarity key for a person or company name: a normalized phonetic fingerprint that collapses spelling variants, transliterations and legal-suffix noise to the same key. Two names sharing a key are likely the same entity. Deterministic, no LLM. For dedup, entity resolution and record linkage across datasets.
Output
A deterministic normalized phonetic fingerprint (similarity key) string for the input name. Two names that resolve to the same key are likely the same entity, regardless of spelling variants, transliterations, or legal suffix differences.
Example use cases
Deduplicate customer records across systems
“I've got customer lists from three different vendors that I'm trying to merge, but the same company shows up with different spellings and legal structures. Can you generate similarity keys for all the company names so I can identify which records are actually duplicates?”
Match supplier names in procurement data
“We're consolidating our supplier database and I notice the same vendors appear under slightly different names—some with 'Inc.' some with 'Co., Ltd.' and some with Japanese transliterations. Can you normalize these names into similarity keys so I can group all variants of the same supplier together?”
Resolve entity names across international datasets
“I'm linking data from our Japan operations with our US headquarters, and many company names are spelled differently or have different legal suffixes depending on which country the record came from. Can you generate phonetic fingerprints for these company names so I can match them accurately across both datasets?”
Technical details
Endpoint
GEThttps://data.japanagent.dev/match/key?utm_source=zero.xyzWhen to prefer
Use this endpoint when you need a deterministic, LLM-free method to deduplicate or link records by name across datasets — especially when names have spelling variants, transliterations, or varying legal suffixes. Prefer this over fuzzy string matching or LLM-based comparison when you need speed, consistency, and reproducibility at scale.
Side effects
- Missing required 'name' query parameter returns a 400 error
- Empty or whitespace-only name may return a null or empty key
- Very short or single-character names may produce low-quality keys
- Non-Latin script names may have inconsistent transliteration results
- Payment failure or insufficient funds returns a 402 error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Tags
x402
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