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gateway.apiosk.com – Data Deduplication (data-clean/dedupe)
x402
gateway.apiosk.com – Data Deduplication (data-clean/dedupe) is a paid API for AI agents from gateway.apiosk.com, paid per call via x402, $0.02/call, status unknown (last checked 2026-09-14).
Deduplicates an array of records by clustering near-duplicate entries based on a similarity threshold, returning cluster assignments for each record.
Price / call$0.02
Success—
StatusUnknown
How this service works
Fuzzy-match a submitted record set and return cluster ids for likely duplicates.
Output
Returns a JSON object with ok status, total record count, per-record cluster assignments (each record gets a cluster_id), and the total number of clusters found. Records sharing the same cluster_id are considered duplicates or near-duplicates of each other.
Example use cases
Clean up duplicate supplier names
“I've got a list of supplier names from our procurement database and I suspect there are a bunch of near-duplicates due to typos and abbreviations — can you run deduplication on them with a similarity threshold of 0.85 and show me which ones are actually the same supplier?”
Merge duplicate address records
“I have thousands of address entries exported from our CRM and a lot of them look like duplicates but with slight variations in spelling or formatting — can you cluster them by similarity so I can figure out which ones refer to the same location and clean up the list?”
Identify duplicate product listings
“We scraped product listings from several sources and I think there are a lot of near-duplicate entries for the same products — can you deduplicate them using a fuzzy similarity threshold of 0.8 and group the ones that seem to be referring to the same product together?”
Technical details
Endpoint
POSThttps://gateway.apiosk.com/data-clean/dedupeWhen to prefer
Choose this endpoint when you need to programmatically deduplicate or cluster an array of records by similarity — especially for entity resolution, data cleaning pipelines, or merging near-duplicate entries. Prefer it over exact-match deduplication when fuzzy/approximate matching is needed, controlled by the threshold parameter.
Side effects
- Empty or missing records array returns an error
- Non-numeric threshold value causes validation failure
- Threshold outside valid range (e.g. >1 or <0) may return error or unexpected clusters
- Very large record arrays may time out or exceed payload limits
- Malformed record objects may cause partial processing or error
- Network/payment failure (x402) if USDC balance is insufficient
Tags
x402
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