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U2A Entity Name Matching
x402
U2A Entity Name Matching is a paid API for AI agents from www.u2a.com.au, paid per call via x402, $0.005/call, status unknown (last checked 2026-10-10).
Fuzzy-matches vendor, fund, company, or account names across two datasets using normalized and conservative similarity scoring.
Price / call$0.005
Success—
StatusUnknown
How this service works
Matches vendor, fund, company, or account names across two datasets using normalized and conservative fuzzy matching.
Output
Returns matched pairs between leftRecords and rightRecords with similarity scores, indicating which names correspond across the two datasets above the specified threshold, along with any unmatched records from either side.
Example use cases
Vendor onboarding name reconciliation
“I have a list of 200 vendors from our ERP and a separate supplier master list from our bank — can you fuzzy-match the company names across both lists using a threshold of 85? The name field in the ERP export is 'vendor_name' and in the bank file it's 'supplier_name'.”
Fund name linking across portfolios
“We have two fund datasets — one from our internal system with a 'fund_label' field and one from our custodian with a 'fund_name' field — can you match them by name similarity using a strict threshold of 92 so we only get high-confidence links?”
Account name deduplication across ledgers
“Our accounts payable team imported records from two different accounting systems and the company names don't quite match due to abbreviations and typos. Can you match the 'account_name' field from the first list against the 'entity_name' field in the second list with a threshold of 80?”
Technical details
Endpoint
POSThttps://www.u2a.com.au/api/mcp/entity-match?utm_source=zero.xyzWhen to prefer
Use this endpoint when you need to link or reconcile entity names (vendors, funds, companies, accounts) across two datasets where names may differ due to abbreviations, typos, formatting differences, or inconsistent conventions — particularly in financial workflows like accounts payable, vendor onboarding, fund administration, or ledger reconciliation. Prefer this over exact-match joins when string equality will miss valid matches.
Side effects
- Threshold set too high (e.g. 100) resulting in zero matches even for near-identical names
- leftNameField or rightNameField not matching actual keys in the provided records, causing errors
- Records arrays exceeding 1000 items per side, hitting the maxItems limit
- Names in completely different languages or scripts producing low similarity scores
- Very short or generic names (e.g. 'Corp', 'Ltd') generating false positives at low thresholds
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| threshold | number | Minimum similarity score (0-100) to count as a match. Higher means stricter. |
| leftRecords | array | Records whose names you want to match, e.g. your vendor list (max 1000). |
| rightRecords | array | Records to match against, e.g. a bank or supplier master list (max 1000). |
| leftNameField | string | Field in leftRecords that holds the company, fund or account name. |
| rightNameField | string | Field in rightRecords that holds the name to compare against. |
Tags
x402
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