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Business Event Participation — String Normalisation + Adjacent Row Changes
x402
Business Event Participation — String Normalisation + Adjacent Row Changes is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-16).
Normalises company_group strings and detects adjacent row changes in attendee_count or company_count for business event participation data (up to 200 rows, 2 reports per call).
Price / call$0.01
Success—
StatusUnknown
How this service works
Business event participation — String normalisation + Adjacent row changes: String normalisation + Adjacent row changes for supplied business event participation records (attendee_count, company_count). 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 structured reports per call: (1) a string normalisation report for the company_group field across all supplied rows, and (2) an adjacent row changes report for the selected numeric field (attendee_count or company_count), covering sequential differences between consecutive rows — all computed locally with no external lookups.
Example use cases
Event series attendance shift detection
“I have weekly event participation records across two company groups over 4 dates — can you check attendee_count for adjacent row changes and also normalise the company_group strings? Rows: row-1, 2026-10-01, group-a, 10 attendees, 1 company; row-2, 2026-10-02, group-B, 20 attendees, 2 companies; row-3, 2026-10-03, Group-A, 15 attendees, 3 companies; row-4, 2026-10-04, group-b, 30 attendees, 4 companies.”
Company count sequential change analysis
“For my business event records, run the two reports on company_count — I want adjacent row changes detected and the company_group strings normalised. Here are the rows: row-1, 2026-11-01, alpha corp, 5 attendees, 3 companies; row-2, 2026-11-02, Beta Corp, 8 attendees, 7 companies; row-3, 2026-11-03, alpha corp, 6 attendees, 2 companies.”
Post-conference data cleanup and diff
“After our conference series, I need to clean up company group labels and spot where attendee_count jumped or dropped between consecutive days. Can you normalise the strings and flag adjacent row changes for these 3 rows: row-A, 2026-09-10, Innovate Hub, 50 attendees, 10 companies; row-B, 2026-09-11, innovate hub, 80 attendees, 12 companies; row-C, 2026-09-12, INNOVATE HUB, 45 attendees, 9 companies?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-19-029?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have tabular business event participation data (up to 200 rows) and need both string normalisation on company group labels AND sequential/adjacent row change detection on a numeric participation metric in a single low-cost call. It is ideal for post-event data cleaning pipelines, attendance trend QA, and lightweight analytical preprocessing where no external data lookup or prediction is needed.
Side effects
- Exceeding 200 rows returns a validation error
- Missing required fields (row_id, company_group, date, attendee_count, company_count) causes schema rejection
- Invalid date format (not YYYY-MM-DD) triggers pattern validation failure
- Numeric values outside ±1,000,000,000,000 are rejected
- Submitting fewer than 1 row fails minItems constraint
- Invalid field enum value (anything other than attendee_count or company_count) causes rejection
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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