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Company Record Completeness — String Normalisation + IQR Outlier Flags
x402
Company Record Completeness — String Normalisation + 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).
Analyzes up to 200 company record completeness rows, producing string normalization and IQR-based outlier flag reports for populated_fields and required_fields metrics.
Price / call$0.01
Success—
StatusUnknown
How this service works
Company record completeness — String normalisation + IQR outlier flags: String normalisation + IQR outlier flags for supplied company record completeness records (populated_fields, required_fields). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.
Output
Two independent analytical reports per call: (1) a string normalization report cleaning and standardizing text fields in the supplied rows, and (2) an IQR outlier flag report identifying which rows have statistically anomalous values in the selected numeric field (populated_fields or required_fields), based purely on the supplied data with no external lookups.
Example use cases
CRM data quality audit for sales team
“I've got 120 company records from our CRM export — each has a company group, a date, and counts of how many fields are populated versus required. Can you normalize the strings and flag any IQR outliers in the populated_fields column so I know which records look suspicious?”
Monthly completeness anomaly detection
“We track record completeness for our two company groups every day in October. Can you run the IQR outlier check on the required_fields values across all 90 rows so I can see which days had abnormal completeness counts?”
Pre-pipeline data hygiene check
“Before I load this company completeness dataset into our pipeline, can you normalize the string fields and flag any outliers using IQR for the populated_fields metric? I have around 180 rows split across three company groups.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-01-032?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need fast, local statistical analysis (IQR outlier detection + string normalization) on batches of up to 200 company record completeness rows without requiring any external data lookups, predictions, or live enrichment. Ideal for pre-pipeline data hygiene, CRM quality audits, and anomaly detection on completeness metrics where cost-efficiency ($0.01 for two reports) and offline analytical processing are priorities.
Side effects
- Exceeding 200 rows returns a validation error
- Missing required fields (row_id, company_group, date, populated_fields, required_fields) causes request rejection
- Invalid date format (not YYYY-MM-DD) fails schema validation
- Numeric values outside allowed range (-1T to 1T) are rejected
- Empty rows array returns an error
- Supplying an invalid field enum value (not 'populated_fields' or 'required_fields') fails validation
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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