Nero Labs Data Aggregate & Pivot

x402

Nero Labs Data Aggregate & Pivot is a paid API for AI agents from x402-agent-tools.nerolabs.workers.dev, paid per call via x402, $0.002/call, status unknown (last checked 2026-10-22).

Groups up to 500 JSON rows and computes per-group statistics (count, sum, avg, min, max, median, distinct count, first, last) with date bucketing, pivot tables, sorting, and top-N filtering.

Price / call$0.002

Seller volume →—

Success—

StatusUnknown

How this service works

Pay-per-call tools for AI agents, 31 in all: read web pages and RSS feeds, OCR, PDF text, transcription; email, phone and domain checks; UK, Irish and Polish company lookups and UK risk reports; website contacts, tech stack and SEO audits; PageSpeed; AI review, job post and row enrichment; data cleaning, joins, dedupe and diffs; US and EU compliance rules. No account or API key: pay each call in USDC on Base over x402.

Output

Returns one row per distinct group combination containing the requested aggregation columns (e.g. sum_sales, count, avg_price), plus a summary object with groupCount, inputRowCount, outputRowCount, column names, warnings, pivot schema, and how many rows were dropped by topN filtering. Optionally includes a totals row covering all input rows.

Example use cases

Monthly revenue rollup by region

“I have 400 transaction records as JSON. Can you group them by region and month, sum up the revenue and count the orders for each group, and sort the results by total revenue descending?”

Pivot table for product sales by country

“Group these 250 sales rows by country, pivot on the product column so each product becomes its own column, and sum the units_sold in each cell — I want a classic pivot table view.”

Top 10 customers by spend

“Aggregate these customer order rows by customer_id, compute the total amount spent and number of orders for each, sort by total_amount descending, and keep only the top 10 customers.”

Technical details

Endpoint

POSThttps://x402-agent-tools.nerolabs.workers.dev/data/aggregate?utm_source=zero.xyz

When to prefer

Choose this endpoint when you have a batch of raw JSON records (up to 500) and need grouped summary statistics, pivot tables, or ranked top-N results without setting up a database or writing SQL. Ideal for ad-hoc reporting, enriching agent pipelines with aggregated signals, or preprocessing data before display. It handles mixed-schema rows and supports date bucketing natively, making it more flexible than a SQL query against a rigid schema. Prefer alternatives if your dataset exceeds 500 rows or if you need joins across multiple tables.

Side effects

More than 500 rows submitted — endpoint enforces a hard cap
More than 20 aggregation functions specified — rejected
pivotField has more than 50 distinct values — rejected
Invalid dot-path in groupByFields — field not found in rows
Aggregation function other than count used without specifying a field — error
Malformed JSON rows array — parse error
Payment not included or insufficient — 402 response

Input

Schema · Request body

Field	Type	Description
rows	array	The records to aggregate, up to 500. Each row is a JSON object; keys may differ between rows.
topN	integer	After sorting, keep only the first N groups. The totals row still covers every input row.
sortBy	string	An output column to sort by: a group field, an aggregation alias such as "total_amount", or a pivot column. Omitted sorts by the group fields.
pivotField	string	Turns this field's distinct values into columns, pivot-table style: group by "region" and pivot on "product" for one row per region with a column per product. Must not also be a group-by field. At most 50 distinct values.
aggregations	array	What to compute per group, for example [{"function":"count","alias":"orders"}, {"field":"amount","function":"sum","alias":"total_amount"}]. Every function except count needs a field. alias is the output column name (defaults to function_field, or "count"). Omitted gives a plain row count per group. Up to 20.
groupByFields	array	One output row per distinct combination of these field values, like SQL GROUP BY, for example ["region"] or ["city", "category"]. Dot paths like "address.city" work. Empty or omitted aggregates every row into a single row.
groupMatching	string	normalized (default) ignores letter case and extra whitespace when grouping, so "South" and "south " are one group. exact requires identical values.
pivotFunction	string	How pivot cell values are combined. Defaults to sum when pivotValueField is set; ignored (row count) without one.
sortDirection	string	asc (default) or desc. Use desc with topN for "top N by" questions.
lenientNumbers	boolean	On by default: "$1,234.50", "49 USD", "12%" and "(300)" count as numbers for sum, avg, min, max and median. Set false to accept only real numbers and plain numeric strings.
dateBucketField	string	A date or timestamp field to group by time period, for example "orderedAt". Adds a group column named like "orderedAt_month". Unreadable dates land in an "(invalid date)" group.
pivotValueField	string	The field whose values fill the pivot cells, for example "amount". Omitted fills each cell with a row count.
includeTotalsRow	boolean	Appends a grand-total row labelled "(total)" and adds a _rowType column ("group" or "total").
dateBucketGranularity	string	Bucket size for dateBucketField: day (2026-08-19), week (2026-W34), month (2026-08, default), quarter (2026-Q3) or year.

Output

Schema · Response

{
  "type": "json",
  "example": {
    "rows": [
      {
        "count": 2,
        "region": "North",
        "sum_sales": 180
      },
      {
        "count": 1,
        "region": "South",
        "sum_sales": 80
      }
    ],
    "summary": {
      "pivot": null,
      "columns": [
        "region",
        "sum_sales",
        "count"
      ],
      "warnings": [],
      "groupCount": 2,
      "aggregations": [
        {
          "alias": "sum_sales",
          "field": "sales",
          "function": "sum"
        },
        {
          "alias": "count",
          "function": "count"
        }
      ],
      "droppedByTopN": 0,
      "groupByFields": [
        "region"
      ],
      "inputRowCount": 3,
      "skippedValues": {},
      "outputRowCount": 2,
      "totalsRowIncluded": false
    },
    "_example_note": "Real output, trimmed: long lists cut to their first items and long text shortened."
  }
}

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