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Company Headcount Observations — String Normalisation + Date by Category Pivot
x402
Company Headcount Observations — String Normalisation + Date by Category Pivot is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-19).
Normalises company name strings and pivots headcount/open_roles observations by date and category group, producing two analytical reports from supplied row data.
Price / call$0.01
Success—
StatusUnknown
How this service works
Company headcount observations — String normalisation + Date by category pivot: String normalisation + Date by category pivot for supplied company headcount observations records (headcount, open_roles). 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 analytical reports: (1) a string-normalised version of the company_group labels across all supplied rows, and (2) a pivot table of the selected field (headcount or open_roles) indexed by date and company_group category — all computed locally from the supplied data with no external lookups.
Example use cases
Quarterly workforce snapshot pivot
“Here are 150 rows of headcount observations across our divisions from Q3, each with a company_group, date, headcount, and open_roles — please normalize the group names and pivot the headcount figures by date and category so I can see the breakdown clearly.”
Open roles trend by business unit
“I've got a dataset of open_roles counts across multiple business units with dates spanning six months — can you normalize the unit name strings and create a date-by-category pivot using the open_roles field?”
Cleaning messy company labels in HR data
“Our HR export has 80 rows where the company_group column has inconsistent capitalisation and spacing — run string normalization on those and also pivot the headcount numbers by date and company group for me.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-12-035?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 rows of company headcount observation records that need both company group string normalization and a date-by-category pivot in a single low-cost call. It is ideal for HR analytics workflows where raw export data has inconsistent company labels and you need a structured time-series pivot without any external data lookups or predictions.
Side effects
- Rows exceeding 200 items will be rejected — trim input to 200 rows maximum
- Missing required fields (row_id, company_group, date, headcount, open_roles) cause validation errors
- Dates not matching YYYY-MM-DD pattern are rejected
- Null values in headcount or open_roles are accepted but may produce gaps in pivot output
- Invalid field enum value (anything other than 'headcount' or 'open_roles') causes a schema error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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