All Services

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 energy dependency analytics data for a given country or region code

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

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

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

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

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

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

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

Searches for books by query and returns relevant book data results

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

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

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

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

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

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

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

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

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

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

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

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.

Filters a supplied set of data pipeline run records to only those where a chosen numeric field (processed_rows or rejected_rows) falls within a specified numeric range.

Computes a secondary-measure weighted mean over up to 200 typed data pipeline run records (processed_rows or rejected_rows) with local descriptive analytics.

Normalises string fields in up to 200 data pipeline run records and returns a local descriptive analytics report on the normalised data.

Computes a rolling/trailing mean time series for data pipeline run metrics (processed rows or rejected rows) over a specified window, grouped by pipeline.

Returns recent academic publications on data quality assessment using Crossref publisher metadata, with DOI references and source attribution.

Returns structured citation records with DOI references and source attribution for data quality assessment topics, sourced from Crossref publisher metadata.

Computes adjacent row-over-row changes and fills missing values (zero, mean, or median) in source_total/target_total reconciliation data, returning 2 analytical reports for up to 200 rows.

Runs two analytical reports on supplied reconciliation data: detects adjacent row-to-row changes and performs keyed dataset comparison between source and target totals, for up to 200 rows.

Computes adjacent row changes and secondary-measure weighted mean analytics on up to 200 supplied data reconciliation records containing source and target totals.

Analyzes supplied data reconciliation records (source_total vs target_total) by computing adjacent row-over-row changes and the correlation between the two measures, returning two independent analytical reports for up to 200 rows.

Runs two analytical reports on supplied reconciliation data: a base-100 indexed series for a chosen numeric field and a date-by-category pivot table, for up to 200 rows.

Reconciles source and target totals across up to 200 rows by computing a Base-100 indexed series and filling missing values using a chosen strategy (zero, mean, or median).

Computes a base-100 indexed time series and a keyed dataset comparison report for two sets of reconciliation records (source_total vs target_total), up to 200 rows each, returning two independent analytical reports.

Computes a base-100 indexed time series and a secondary-measure weighted mean for supplied source/target reconciliation data rows, returning two analytical reports in one call.

Computes category frequency distributions and a base-100 indexed series for up to 200 data reconciliation rows comparing source_total vs target_total values.

Computes two analytical reports — category frequency distribution and daily sum time series — for supplied data reconciliation records comparing source and target totals.

Generates two analytical reports — category frequency counts and a date-by-category pivot table — from supplied data reconciliation records containing source and target totals.

Compares two datasets of up to 200 rows, producing category frequency distributions and a keyed row-level comparison report to surface reconciliation discrepancies between source and target totals.

Analyzes data reconciliation records (source_total vs target_total) by computing category frequencies across dataset groups and filtering rows by a numeric interval, returning two bundled local analytical reports.

Computes category frequency distribution and a trailing moving average series for supplied data reconciliation records (source_total vs target_total) in a single call.

Analyzes data reconciliation records to produce category frequency distributions and a two-measure correlation report between source_total and target_total values.

Generates two analytical reports (daily sum time series and base-100 indexed series) from supplied source/target reconciliation data, up to 200 rows, for $0.01 USDC.

Computes daily sum time series and flags IQR-based outliers for source_total and target_total reconciliation records supplied by the caller.

Runs two analytical reports on supplied reconciliation data: a daily sum series aggregation and a keyed dataset comparison between source and target totals, for up to 200 rows.

Computes a daily sum series and a secondary-measure weighted mean for up to 200 rows of supplied source/target reconciliation data, returning two independent analytical reports per call.

Computes daily sum series and trailing mean series analytics for supplied data reconciliation records comparing source and target totals, returning two independent reports for up to 200 rows.

Computes a daily sum time series and a two-measure correlation analysis for supplied source_total and target_total reconciliation data, returning two independent analytical reports for up to 200 rows.

Pivots reconciliation rows by date and dataset group, then fills missing source_total or target_total values using zero, mean, or median imputation — returning two analytical reports for up to 200 rows.

Analyzes up to 200 reconciliation rows to produce two reports: a duplicate key detection report and an adjacent row change analysis for source and target totals.

Generates two analytical reports from supplied reconciliation rows: a duplicate key report and a date-by-category pivot table comparing source and target totals.

Identifies duplicate row keys and fills missing values (via zero, mean, or median) in up to 200 reconciliation records comparing source_total and target_total fields.

Analyzes up to 200 reconciliation rows to produce a duplicate key report and a grouped numeric summary for source_total or target_total values.

Generates two analytical reports — a duplicate key report and a numeric distribution — for up to 200 data reconciliation rows containing source and target totals.

Generates two analytical reports for supplied reconciliation data: a duplicate key report and a numeric interval filter, across up to 200 rows of source/target totals.

Analyzes up to 200 data reconciliation rows to produce a duplicate key report and a numeric row ordering report for source_total or target_total values.

Analyzes up to 200 reconciliation rows to produce a duplicate key report and a secondary-measure weighted mean, using local analytical engines with no external lookups.

Generates two local analytical reports for data reconciliation rows: a duplicate key report and a trailing mean series, for up to 200 source/target records.

Analyzes up to 200 reconciliation records to produce a duplicate key report and a Pearson/linear correlation report between source_total and target_total values.

Generates two analytical reports for data reconciliation records — an equal-width histogram of a chosen numeric field and a date-by-category pivot table — for up to 200 rows of source/target totals.

Generates an equal-width histogram and fills missing values (zero/mean/median) for source_total and target_total reconciliation data across up to 200 rows, producing 2 analytical reports locally.

Analyzes up to 200 reconciliation records by generating an equal-width histogram of a chosen field and a keyed row-by-row comparison between two datasets.

Runs two analytical reports (equal-width histogram and secondary-measure weighted mean) on supplied source/target reconciliation data rows, up to 200 rows per call.