All Services

Analyzes data ingestion batch records (received_rows, accepted_rows) to produce IQR-based outlier flags and a secondary-measure weighted mean, across up to 200 rows in two independent reports.

Compares two keyed datasets of data ingestion batch records (received_rows, accepted_rows) and fills in explicit missing values, producing two analytical reports for up to 200 rows.

Analyzes data ingestion batch records to produce a numeric distribution report and an adjacent row changes report for received_rows or accepted_rows fields.

Computes numeric distribution statistics and category frequency counts for data ingestion batch records (received_rows, accepted_rows) across up to 200 rows.

Analyzes up to 200 data ingestion batch records by computing a numeric distribution report and filling missing values in received_rows or accepted_rows using a chosen fill method (zero, mean, or median).

Generates two analytical reports (numeric distribution and grouped numeric summary) for data ingestion batch records covering received_rows and accepted_rows fields, across up to 200 rows.

Computes numeric distribution statistics and applies a numeric interval filter on received_rows and accepted_rows fields across up to 200 data ingestion batch records.

Analyzes up to 200 data ingestion batch records by computing numeric distribution statistics and row ordering reports for received_rows and accepted_rows fields.

Computes a numeric distribution report and a trailing mean time series for received_rows or accepted_rows across up to 200 data ingestion batch records.

Runs numeric distribution analysis and two-measure correlation reports on data ingestion batch records (received_rows and accepted_rows) for up to 200 rows.

Filters data ingestion batch records by a numeric interval on received_rows or accepted_rows, and identifies adjacent row changes, returning two analytical reports for up to 200 rows.

Analyzes data ingestion batch records by filtering rows within a numeric interval and computing a base-100 index series for either received_rows or accepted_rows fields.

Filters data ingestion batch records by a numeric range and produces a date-by-category pivot table for received_rows or accepted_rows, returning two analytical reports for up to 200 rows.

Analyzes up to 200 data ingestion batch records by applying a numeric interval filter and comparing two keyed datasets on received_rows or accepted_rows fields.

Filters data ingestion batch records by a numeric interval on a chosen field and computes a weighted mean of a secondary measure, returning two analytical reports for up to 200 rows.

Filters data ingestion batch records by a numeric interval and computes the correlation between received_rows and accepted_rows for up to 200 rows, returning two independent analytical reports.

Runs two analytical reports on up to 200 data ingestion batch records: numeric row ordering and adjacent row changes for received_rows or accepted_rows fields.

Computes numeric row ordering and base-100 index series for data ingestion batch records (received_rows, accepted_rows) across up to 200 rows.

Produces two offline analytical reports for supplied data ingestion batch records: numeric row ordering and a daily sum time series for received_rows or accepted_rows (up to 200 rows).

Produces two analytical reports for data ingestion batch records: a numeric row ordering and a date-by-category pivot, for up to 200 rows of received/accepted row counts.

Analyzes data ingestion batch records by producing a numeric row ordering report and an equal-width histogram for received_rows or accepted_rows values across up to 200 rows.

Sorts data ingestion batch records numerically by row and fills missing values in received_rows or accepted_rows using zero, mean, or median imputation, producing two analytical reports for up to 200 rows.

Ranks and IQR-flags received_rows or accepted_rows values across up to 200 data ingestion batch records, returning two analytical reports per call.

Sorts and filters supplied data ingestion batch records by received_rows or accepted_rows values, returning two analytical reports: ranked ordering and interval-filtered results.

Computes numeric row ordering and trailing mean series for up to 200 data ingestion batch records across received_rows and accepted_rows fields.

Analyzes up to 200 data ingestion batch records by ranking rows numerically and computing correlation between received_rows and accepted_rows.

Performs a two-report analysis on up to 200 data ingestion batch records: a record quality audit and adjacent row change detection for received_rows or accepted_rows fields.

Runs two analytical reports on data ingestion batch records: a record quality audit (accepted vs. received rows) and a category frequency breakdown by dataset group.

Runs two local analytical reports on up to 200 data ingestion batch records: a record quality audit and a daily sum time series for received_rows or accepted_rows.

Runs two analytical reports on supplied data ingestion batch records: a record quality audit (checking received_rows vs accepted_rows integrity) and a date-by-category pivot table, for up to 200 rows.

Runs a record quality audit and exact row deduplication on up to 200 data ingestion batch records (received_rows, accepted_rows), returning two independent analytical reports.

Runs three local analytical reports on up to 200 data ingestion batch records: record quality audit, exact row deduplication, and base-100 index series for received_rows or accepted_rows.

Runs three analytical reports on up to 200 data ingestion batch records: a record quality audit, exact row deduplication, and a duplicate key report — all from supplied data, no external lookups.

Runs three analytical reports on data ingestion batch records: record quality audit, exact row deduplication, and grouped numeric summary for received_rows or accepted_rows.

Runs three analytical reports (record quality audit, exact row deduplication, and numeric distribution) on up to 200 data ingestion batch records containing received_rows and accepted_rows fields.

Runs three independent analytical reports (record quality audit, exact row deduplication, and numeric row ordering) on a batch of data ingestion records containing received_rows and accepted_rows fields.

Runs three analytical reports (record quality audit, exact row deduplication, and trailing mean series) on supplied data ingestion batch records (received_rows, accepted_rows) for up to 200 rows.

Audits record quality and fills missing values (received_rows or accepted_rows) in up to 200 data ingestion batch records using local analytical engines, returning two independent reports.

Performs a two-part quality audit on data ingestion batch records: a record quality check and IQR-based outlier flagging for received_rows or accepted_rows fields across up to 200 rows.

Runs two analytical reports on data ingestion batch records: a record quality audit and a numeric distribution summary for received_rows or accepted_rows fields across up to 200 rows.

Runs two analytical reports on up to 200 data ingestion batch records: a record quality audit and a numeric interval filter on received_rows or accepted_rows values.

Audits record quality and provides numeric row ordering for data ingestion batch records containing received_rows and accepted_rows fields, returning two analytical reports for up to 200 rows.

Runs three analytical reports (record quality audit, string normalisation, and adjacent row change detection) on up to 200 data ingestion batch rows covering received_rows and accepted_rows fields.

Runs three local analytical reports on data ingestion batch records: a record quality audit, string normalisation, and a base-100 index series for received_rows or accepted_rows fields.

Runs three analytical reports (record quality audit, string normalisation, and category frequencies) on up to 200 data ingestion batch rows containing received_rows and accepted_rows fields.

Runs three analytical reports on data ingestion batch records: a record quality audit, string normalisation, and a daily sum series for received_rows or accepted_rows fields.

Runs three analytical reports on up to 200 data ingestion batch rows: a record quality audit, string normalisation, and a date-by-category pivot for received_rows or accepted_rows.

Runs three independent analytical reports on data ingestion batch records: a record quality audit, string normalisation, and a duplicate key report — all offline, no external calls.

Runs three local analytical reports (record quality audit, string normalisation, and equal-width histogram) on up to 200 data ingestion batch records containing received_rows and accepted_rows fields.

Runs three analytical reports on up to 200 data ingestion batch rows: a record quality audit, string normalization, and exact row deduplication — all using local engines with no external lookups.

Runs three analytical reports on supplied data ingestion batch records: a record quality audit, string normalisation, and keyed comparison between two datasets — all locally, with no external calls.

Runs three analytical reports (record quality audit, string normalisation, and numeric distribution) on up to 200 data ingestion batch rows containing received_rows and accepted_rows metrics.

Runs three independent analytical reports (record quality audit, string normalisation, and numeric row ordering) on up to 200 rows of data ingestion batch records containing received_rows and accepted_rows fields.

Runs three local analytical reports on data ingestion batch records: a record quality audit, string normalisation, and a secondary-measure weighted mean for received_rows or accepted_rows fields.

Runs three analytical reports on data ingestion batch records: a record quality audit, string normalisation, and trailing mean series computation for received_rows and accepted_rows fields.

Runs a record quality audit and Pearson/Spearman correlation analysis between received_rows and accepted_rows for up to 200 data ingestion batch records, returning two independent analytical reports.

Computes a secondary-measure weighted mean and a date-by-category pivot table for up to 200 data ingestion batch records (received_rows, accepted_rows) using local analytical engines.

Computes a secondary-measure weighted mean and fills missing values for up to 200 data ingestion batch records (received_rows, accepted_rows), returning two analytical reports per call.

Computes a secondary-measure weighted mean and performs a keyed dataset comparison across up to 200 data ingestion batch records (received_rows, accepted_rows).

Runs two local analytical reports on supplied data ingestion batch records: string normalisation and daily sum series for received_rows or accepted_rows fields.

Runs string normalisation and a date-by-category pivot analysis on up to 200 rows of data ingestion batch records (received_rows, accepted_rows), returning two local analytical reports.

Analyzes up to 200 data ingestion batch records to produce two independent reports: string normalization and duplicate key detection.

Normalises strings and deduplicates exact rows in data ingestion batch records (received_rows, accepted_rows), producing 2 analytical reports for up to 200 rows.

Normalises string fields and fills missing values in data ingestion batch records (received_rows, accepted_rows) for up to 200 rows, returning 2 analytical reports.

Normalises string fields and produces a grouped numeric summary for up to 200 data ingestion batch records (received_rows, accepted_rows) in two independent analytical reports.

Runs string normalisation on dataset_group and numeric distribution analysis on received_rows or accepted_rows for up to 200 data ingestion batch records, returning two independent analytical reports.

Computes a trailing mean time series and a keyed dataset comparison for up to 200 data ingestion batch records across received_rows and accepted_rows metrics.

Computes a trailing mean time series and a secondary-measure weighted mean for up to 200 data ingestion batch records (received_rows, accepted_rows) using local analytical engines.

Computes Pearson correlation between received_rows and accepted_rows across up to 200 data ingestion batch records, while filling missing values using zero, mean, or median imputation, and returns two analytical reports.

Computes Pearson/rank correlation between received_rows and accepted_rows, and compares two keyed data ingestion batch datasets, returning two independent analytical reports for up to 200 rows.

Returns debt burden analytics data for a specified country or region code, covering trade, market, and financial metrics.

Retrieves metadata and information for a specific named dataset (e.g. EU cereal prices, oilseeds prices, pigmeat prices) by dataset ID

Returns energy dependency analytics data for a given country or region code

Returns trade and market analytics broken down by country structure for a given country code

Returns the current market volatility regime classification and related analytics based on a configurable historical lookback window.

Performs a web search query and returns ranked results from the web, suitable for AI agent consumption.

Translates text into a specified target language, payable with USDC via x402 on Base chain

Fetches top news articles matching a given query string, paid per-call via x402 on Base chain

Searches for news articles matching a query and returns results via a multi-source news aggregation pipeline

Searches news articles across multiple sources based on a text query, returning relevant news results for AI agents.

Performs a web search query and returns ranked results, paid per-call via x402 on Base chain

Fetches and extracts content from a given URL, returning parsed page data for AI agent consumption

Searches for images across the web based on a text query and returns matching image results

Searches for videos across the web based on a query string and returns a list of video results

Search for books by query string and return a list of matching book results

Fetches top news articles matching a search query, paid via x402 on Base chain

Searches news articles by query string, returning relevant news results for AI agents via x402 micropayment on Base chain

Searches for books by query and returns relevant book data results

Searches for videos across the web based on a query string and returns ranked results

Searches and retrieves news articles matching a given query, returning structured results via x402 micropayment on Base chain

Computes adjacent (period-over-period) row changes for data pipeline run metrics (processed and rejected rows) across up to 200 supplied records.

Computes daily sum totals for data pipeline run metrics (processed rows or rejected rows) across up to 200 supplied typed records, grouped by pipeline and date.

Analyzes up to 200 data pipeline run records and returns a duplicate key report identifying repeated row identifiers across pipeline runs.

Computes a bounded equal-width histogram over processed_rows or rejected_rows fields for up to 200 data pipeline run records, returning local descriptive analytics with configurable bin count.

Removes exact duplicate rows from up to 200 data pipeline run records (by pipeline, date, processed_rows, rejected_rows) and returns a deduplication report.

Fills missing numeric values (processed_rows or rejected_rows) in up to 200 data pipeline run records using zero, mean, or median imputation.

Computes a grouped numeric summary (descriptive statistics) for data pipeline run metrics, grouped by pipeline name, from up to 200 supplied records.

Detects IQR-based statistical outliers in data pipeline run metrics (processed_rows or rejected_rows) across up to 200 typed records

Compares two keyed datasets of data pipeline run records (processed/rejected rows per pipeline per date) and returns a descriptive analytics comparison report.

Computes a local descriptive numeric distribution report (e.g. min, max, mean, percentiles, histogram) for a chosen numeric field across up to 200 data pipeline run records.