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Travel Administration Data Quality Suite: Record Audit, String Normalisation & Dataset Comparison
x402
Travel Administration Data Quality Suite: Record Audit, String Normalisation & Dataset Comparison is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-26).
Runs three local analytical reports on travel administration records (trip_count, recorded_cost): record quality audit, string normalisation, and keyed dataset comparison — up to 200 rows per call.
Price / call$0.01
Success—
StatusUnknown
How this service works
Travel administration — Record quality audit + String normalisation + Keyed dataset comparison: Record quality audit + String normalisation + Keyed dataset comparison for supplied travel administration records (trip_count, recorded_cost). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.
Output
Three structured analytical reports returned together: (1) a record quality audit flagging nulls, out-of-range values, and structural issues per row; (2) a string normalisation report showing standardised versions of text fields like team_group; (3) a keyed dataset comparison report showing row-by-row differences between the primary and comparison datasets matched on row_id. No external lookups or predictions are made — all analysis is local.
Example use cases
Pre-load travel data validation
“Before we import this month's travel logs into the warehouse, can you audit these 80 rows of trip records for quality issues, normalise the team_group strings, and compare them against last month's dataset keyed by row_id? Fields are row_id, team_group, date, trip_count, and recorded_cost.”
Expense reconciliation between two teams
“We have two exports of recorded travel costs for Q3 — one from Finance and one from Operations — each with about 120 rows including row_id, team_group, date, trip_count, and recorded_cost. Can you compare them to find discrepancies, normalise the string fields, and flag any quality problems?”
Travel budget anomaly investigation
“Something looks off in our travel admin data. Can you run a data quality audit and string normalisation on these 40 rows of trip_count and recorded_cost entries, and also compare them to our reference dataset by row_id to see where values differ?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-operations-14-207?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need all three of record quality auditing, string normalisation, and keyed dataset comparison performed together on travel administration data (trip_count and recorded_cost fields) in a single low-cost call. It is ideal for pre-ingestion data validation, reconciliation between two data exports, or routine data hygiene checks on travel records up to 200 rows. It is not suitable for live data lookups, predictive analytics, external enrichment, or datasets larger than 200 rows.
Side effects
- Exceeding 200 rows in either dataset returns a validation error
- Rows missing required fields (row_id, team_group, date, trip_count, recorded_cost) are rejected
- Malformed date strings not matching YYYY-MM-DD pattern cause schema validation failure
- Numeric fields outside the allowed range (-1e12 to 1e12) are rejected
- Empty datasets (minItems:1 not met) return an error
- Payment failure or insufficient USDC balance prevents processing
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| other | array |
Tags
x402
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