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Trixie Lasagne Entity Deduplication
x402
Trixie Lasagne Entity Deduplication is a paid API for AI agents from trixielasagne-api.purplewater-b02e2643.eastus.azurecontainerapps.io, paid per call via x402, $0.01/call, status unknown (last checked 2026-09-13).
Detects and groups duplicate records within a dataset using deterministic transitive closure grouping
Price / call$0.01
Success—
StatusUnknown
How this service works
Deterministic within-dataset duplicate detection via transitive grouping
Output
Returns grouped clusters of records identified as duplicates within the submitted dataset, using deterministic transitive grouping logic. Each group contains records that directly or transitively match one another, allowing the caller to identify canonical entities and remove redundant entries.
Example use cases
Customer list deduplication before CRM import
“I'm about to import 5,000 customer records into our CRM and I know there are duplicates — can you deduplicate this JSON list and group any records that refer to the same customer so I can review the clusters before importing?”
Vendor record consolidation for procurement
“We have a vendor dataset with duplicate entries from multiple data sources — please run a deterministic dedupe on this JSON body and group all records that transitively match the same vendor into clusters.”
Deduplicating event log entries
“I have a log of user events exported as JSON and there are repeated entries caused by retries — can you group the duplicate event records together using transitive deduplication so I can count unique events accurately?”
Technical details
Endpoint
POSThttps://trixielasagne-api.purplewater-b02e2643.eastus.azurecontainerapps.io/entity/dedupeWhen to prefer
Choose this endpoint when you need deterministic, reproducible deduplication within a single dataset — where the same input always yields the same output. Ideal when you need transitive grouping (A matches B, B matches C, so A/B/C form one cluster) rather than simple pairwise comparison. Prefer this over cross-dataset matching endpoints when all records are in one dataset. Use over probabilistic/ML-based deduplication when consistency and auditability matter more than recall on fuzzy cases.
Side effects
- Malformed or missing body payload returns a 400-level error
- Non-JSON body with bodyType set to json causes a parse error
- Empty dataset returns no duplicate groups
- Records with no overlapping fields may yield no matches
- Transitive chain errors if entity fields are inconsistently formatted
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Tags
x402
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