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Company Headcount Observations — String Normalisation + Daily Sum Series
x402
Company Headcount Observations — String Normalisation + Daily Sum Series 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).
Normalises company name strings and computes daily sum time series for headcount or open_roles observations across up to 200 supplied rows, returning two analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Company headcount observations — String normalisation + Daily sum series: String normalisation + Daily sum series 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
Returns two reports: (1) a string-normalised version of the company_group field across all supplied rows, and (2) a daily sum time series for the selected field (headcount or open_roles), aggregated per date across all company groups in the supplied data. No external data sources are consulted.
Example use cases
Clean HR data before reporting
“I have 120 headcount observation rows with messy company group names — can you normalise those strings and give me a daily sum series for headcount so I can plug the clean totals into our weekly HR report?”
Daily open roles trend by company
“Here are 80 hiring pipeline records with company_group, date, and open_roles fields. Can you normalise the company names and compute a daily total open_roles series so I can see how our hiring demand changes day by day?”
Validate and aggregate workforce snapshot
“I've got a dataset of 150 company headcount observations that may have inconsistent employer name formats — please normalise the company_group strings and produce a daily sum series for headcount so I can spot any anomalies across the timeline.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-12-027?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have a batch of up to 200 company headcount or open_roles observation records that need both string normalisation of company names and daily aggregation into a sum series — delivered together as two reports in a single low-cost call. Prefer this over general-purpose analytics when you specifically need the combination of text normalisation and time-series daily summation on HR workforce data without any external lookups or predictions.
Side effects
- Rows exceeding 200 items will be rejected due to maxItems constraint
- Missing required fields (row_id, company_group, date, headcount, open_roles) will cause validation errors
- Invalid date format (not YYYY-MM-DD) will fail schema pattern validation
- Null values in headcount or open_roles may affect sum accuracy in the daily series
- Supplying an invalid field enum value (not 'headcount' or 'open_roles') will cause an error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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