Partnership Pipeline — Record Quality Audit + String Normalisation + Two-Measure Correlation is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-15).
Runs three analytical reports on partnership pipeline data: record quality audit, string normalisation, and correlation between qualified_partners and active_partners metrics, for up to 200 rows.
Partnership pipeline — Record quality audit + String normalisation + Two-measure correlation: Record quality audit + String normalisation + Two-measure correlation for supplied partnership pipeline records (qualified_partners, active_partners). 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.
Returns three independent analytical reports: (1) a record quality audit flagging missing values, out-of-range numbers, malformed dates, or structural issues per row; (2) a string normalisation report showing standardised versions of text fields like company_group; and (3) a two-measure correlation report quantifying the statistical relationship between qualified_partners and active_partners across all supplied rows. No external data or live lookups are used — all analysis is performed on the supplied rows only.
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-09-204?utm_source=zero.xyzChoose this endpoint when you need to run three complementary data-quality and analytical operations on partnership pipeline data in a single low-cost API call, rather than calling separate endpoints for each report. It is ideal for batch pre-processing of CRM exports, pipeline snapshots, or periodic data validation workflows involving up to 200 rows with qualified_partners and active_partners fields. Prefer it over manual inspection or generic ETL tools when you want structured reports on string normalisation, record quality, and metric correlation without involving external data sources or prediction models.
| Field | Type | Description |
|---|---|---|
| rows | array |
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