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Company Record Completeness – Quality Audit, Deduplication & IQR Outlier Flags
x402
Company Record Completeness – Quality Audit, Deduplication & IQR Outlier Flags 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 company record completeness data (populated_fields, required_fields): a record quality audit, exact row deduplication, and IQR-based outlier flagging — all on supplied rows, no external lookups.
Price / call$0.01
Success—
StatusUnknown
How this service works
Company record completeness — Record quality audit + Exact row deduplication + IQR outlier flags: Record quality audit + Exact row deduplication + IQR outlier flags for supplied company record completeness records (populated_fields, required_fields). 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
Returns three independent analytical reports: (1) a record quality audit identifying completeness issues in the supplied rows, (2) an exact row deduplication report identifying repeated records, and (3) IQR outlier flags identifying statistically anomalous values in the selected field (populated_fields or required_fields). All computed locally on the supplied data with no external lookups.
Example use cases
CRM data quality audit before migration
“I'm about to migrate our CRM company records and want to check data quality first — can you run a quality audit, find any exact duplicate rows, and flag IQR outliers on the populated_fields values for these 120 company records I'm uploading?”
Identify anomalous company groups in completeness tracking
“We track record completeness scores by company_group every day — can you analyze these 80 rows and flag any company groups with outlier required_fields values using IQR, and also deduplicate in case any rows got logged twice?”
Validate completeness scores before executive reporting
“Before I present our data completeness report to leadership, can you run a quality audit and outlier check on the required_fields metric across these 60 company records to make sure there are no bad data points or duplicates skewing the numbers?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-01-220?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need all three data quality operations — record quality auditing, exact deduplication, and IQR outlier flagging — applied to company record completeness data (populated_fields and required_fields) in a single low-cost call. Ideal for pre-migration checks, periodic data hygiene, or pre-reporting validation on batches up to 200 rows. Not suitable if you need live data enrichment, ML-based anomaly detection, or external company data lookups.
Side effects
- Fewer than 1 row supplied — minimum 1 row required
- More than 200 rows supplied — maximum is 200 rows per call
- Invalid date format (not YYYY-MM-DD) causes validation rejection
- Missing required fields (row_id, company_group, date, populated_fields, required_fields) causes schema error
- null values in numeric fields may reduce outlier detection accuracy
- Insufficient row variance may yield trivial IQR results
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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