All Services

Filters transaction fee observation rows to a numeric interval and fills missing values in fee_units or transaction_count using zero, mean, or median imputation, returning up to 2 analytical reports for up to 200 rows.

Applies a numeric interval filter and IQR-based outlier detection to user-supplied transaction fee observation records, returning up to 2 analytical reports for up to 200 rows.

Computes numeric row ordering and transaction-count-weighted mean for up to 200 transaction fee observation records, returning two analytical reports.

Audits up to 200 rows of transaction fee observation records for data quality issues and flags IQR-based outliers across fee_units or transaction_count fields.

Runs three local analytical reports on up to 200 transaction fee observation rows: record quality audit, string normalisation, and exact row deduplication.

Runs three local analytical reports on transaction fee observation records: a record quality audit, string normalisation, and IQR-based outlier detection on a chosen numeric field.

Runs three local analytical reports (record quality audit, string normalisation, and keyed dataset comparison) on up to 200 rows of transaction fee observation data (fee_units, transaction_count).

Runs three local analytical reports (record quality audit, string normalisation, and numeric distribution) on up to 200 rows of transaction fee observation data containing fee_units and transaction_count fields.

Runs a record quality audit and trailing mean series analysis on up to 200 rows of transaction fee observation data (fee_units, transaction_count).

Runs string normalisation and equal-width histogram analysis on up to 200 transaction fee observation records (fee_units or transaction_count).

Computes a trailing mean time series and a Base-100 indexed series for supplied transaction fee or transaction count observations, returning two analytical reports from local engines.

Computes a trailing mean time series and fills missing values in transaction fee observation records using a chosen fill method (zero, mean, or median).

Computes a trailing moving-average series and a two-measure Pearson/rank correlation report for up to 200 rows of supplied transaction fee observation data (fee_units, transaction_count).

Computes adjacent-period changes in transaction fee share of Bitcoin mining rewards across a series of supplied block rows

Rebases a series of transaction-fee-to-mining-reward share values against a chosen base index point, outputting a Base-100 indexed series for comparative analysis.

Calculates the fee-to-reward share ratio for up to 200 Bitcoin mining reward scenarios in a single batch call, using supplied fee and subsidy values.

Computes and compares transaction fee share in Bitcoin mining rewards before and after a change in fee and subsidy values.

Computes and returns a distribution histogram showing the share of transaction fees within total mining rewards across a set of block-level inputs.

Analyzes a batch of Bitcoin mining reward records and flags which fee/subsidy observations are statistical outliers using the interquartile range (IQR) method.

Generates a one-input sensitivity table showing how transaction fees as a share of total mining reward vary across a range of fee or subsidy values.

Analyzes the ordered trend of transaction fees as a share of total mining reward (fees + subsidy) across a supplied series of Bitcoin block data points.

Ranks submitted Bitcoin block records by the ratio of transaction fees to total mining reward (fees + subsidy), given user-supplied fee and subsidy values.

Computes how a change in transaction fee and block subsidy inputs sequentially affects mining reward share distribution, using a waterfall attribution model.

Classifies transaction-fee-to-subsidy ratio data points against user-defined lower and upper thresholds, producing a bounded threshold classification report for Bitcoin mining fee reward share analysis.

Looks up on-chain transaction details by querying live consensus state via the AmanChain node, paid per call via x402 in USDC.

Analyzes transcript preparation records by computing adjacent row changes and filling missing values explicitly, returning two analytical reports for up to 200 rows.

Runs two analytical reports on transcript preparation data: detects adjacent row changes and performs keyed dataset comparison across up to 200 rows of transcribed_minutes and source_minutes.

Analyzes up to 200 transcript preparation records by computing adjacent row changes and two-measure correlation between transcribed_minutes and source_minutes.

Computes a base-100 indexed time series and a date-by-category pivot table for transcript preparation data (transcribed_minutes and source_minutes) across up to 200 rows.

Analyzes transcript preparation records (transcribed_minutes vs source_minutes) by generating a Base-100 index series and a keyed dataset comparison report for up to 200 rows.

Runs two analytical reports on transcript preparation data: category frequency counts and a date-by-category pivot, for up to 200 rows of transcribed_minutes or source_minutes.

Runs two local analytical reports on transcript preparation records: category frequency distribution and keyed dataset comparison between two supplied row arrays (up to 200 rows each).

Computes a daily sum time series and adjacent row-over-row changes for transcript preparation records (transcribed_minutes, source_minutes) across up to 200 rows.

Computes a daily sum time series and an equal-width histogram for transcribed_minutes or source_minutes fields across up to 200 transcript preparation records.

Computes daily sum series and trailing mean series for transcript preparation records (transcribed_minutes and source_minutes) across up to 200 rows.

Analyzes transcript preparation records to detect duplicate row_id keys and produce an equal-width histogram over transcribed_minutes or source_minutes, returning two independent analytical reports for up to 200 rows.

Generates two analytical reports (equal-width histogram and date-by-category pivot) on transcript preparation records containing transcribed_minutes and source_minutes fields.

Deduplicates transcript preparation records by exact row match and generates a duplicate key report for transcribed_minutes and source_minutes fields across up to 200 rows.

Computes a grouped numeric summary and category frequency report for transcript preparation records (transcribed_minutes, source_minutes) across up to 200 rows.

Generates two analytical reports for transcript preparation data: a grouped numeric summary and a date-by-category pivot, for up to 200 rows of transcribed_minutes and source_minutes data.

Analyzes transcript preparation records (transcribed_minutes, source_minutes) to flag IQR-based outliers and fill missing values using a chosen method, producing two analytical reports for up to 200 rows.

Runs IQR-based outlier detection and keyed dataset comparison on transcript preparation records (transcribed_minutes, source_minutes) for up to 200 rows, returning two independent analytical reports.

Runs IQR-based outlier detection and Pearson/Spearman correlation analysis on up to 200 transcript preparation records with transcribed_minutes and source_minutes fields.

Compares two transcript datasets by row key and fills missing values in transcribed_minutes or source_minutes fields, producing two analytical reports for up to 200 rows.

Generates two local analytical reports (numeric distribution and daily sum time series) for transcript preparation records containing transcribed_minutes and source_minutes fields.

Runs two analytics reports on transcript preparation records: a numeric distribution of a selected minute field and a keyed comparison between two datasets, for up to 200 rows.

Sorts transcript preparation records by a chosen numeric field and flags statistical outliers using the interquartile range (IQR) method, producing two independent analytical reports for up to 200 rows.

Audits data quality and removes exact duplicate rows from transcript preparation records containing transcribed_minutes and source_minutes fields, returning two independent analytical reports.

Runs three analytical reports on transcript preparation records: a record quality audit, exact row deduplication check, and adjacent row change detection for transcribed_minutes and source_minutes fields.

Runs three local analytical reports on transcript preparation records: a record quality audit, exact row deduplication, and category frequency analysis for up to 200 rows.

Runs three analytical reports on transcript preparation records: record quality audit, exact row deduplication, and duplicate key detection — up to 200 rows per call.

Runs three local analytical reports on transcript preparation records: a record quality audit, exact row deduplication, and a grouped numeric summary of transcribed_minutes or source_minutes fields.

Runs three analytical reports (record quality audit, string normalisation, and adjacent row changes) on up to 200 transcript preparation rows containing transcribed_minutes and source_minutes fields.

Runs three analytical reports on transcript preparation records: a record quality audit, string normalisation, and duplicate key detection — all from supplied data, no external lookups.

Audits record quality, normalises strings, and compares two keyed transcript datasets (transcribed_minutes vs source_minutes) for up to 200 rows, returning 3 independent analytical reports.

Audits record quality, normalises strings, and filters by numeric interval for up to 200 transcript preparation rows containing transcribed_minutes and source_minutes fields.

Audits record quality and computes two-measure correlation between transcribed_minutes and source_minutes for up to 200 transcript preparation rows, returning two analytical reports.

Analyzes up to 200 transcript preparation records (transcribed_minutes, source_minutes) producing two reports: string normalization and adjacent row change detection.

Computes trailing mean series and base-100 indexed series for transcript preparation metrics (transcribed_minutes, source_minutes) over up to 200 supplied rows.

Computes a trailing mean time series and fills missing values in transcript preparation records (transcribed_minutes, source_minutes) for up to 200 rows.

Validates a CSV file of transfer records and identifies blank/empty rows, supporting up to 1000 rows with configurable delimiters and cell constraints.

Validates calendar date fields in a CSV of transfer records, checking up to 1000 rows for date format correctness and contract compliance.

Validates a CSV of transfer records and computes per-column statistics (min, max, distribution, categories) for up to 1000 rows.

Validates a declared CSV table of transfer records (up to 1000 rows) against a contract, checking structure, value ranges, categories, and cell formatting.

Validates a CSV file of transfer records against a declared column contract, projecting and checking up to 1000 rows for structural and value conformance.

Validates a CSV of transfer records and reports exact row duplicates, checking up to 1000 rows against a declared schema contract.

Validates the header contract (column names, data types, value ranges, and category constraints) of a CSV file containing transfer records, returning a detailed check report.

Validates a CSV file representing transfer records and returns a report identifying all invalid/non-conforming rows, up to 1000 rows.

Validates numeric columns in a transfer record CSV against declared minimum/maximum bounds, returning a range-check report for up to 1000 rows.

Validates that all record keys (transfer_id) in a submitted CSV of transfer records are unique, returning a uniqueness report for up to 1000 rows.

Validates that all required cells in a transfer record CSV are present and non-empty, supporting up to 1000 rows.

Validates a CSV table of transfer records and flags cells containing spreadsheet formula injections (e.g. cells starting with =, +, -, @).

Validates and normalizes a CSV of transfer records (up to 1000 rows), parsing and type-converting fields like transfer IDs, dates, asset categories, and amounts with configurable bounds and delimiter options.

Validates a CSV table of transfer records for whitespace anomalies, checking up to 1000 rows with support for quoted cells and configurable delimiters.

Analyzes transformation throughput records (processed_rows, duration_seconds) to produce two reports: adjacent row changes and a date-by-category pivot table, for up to 200 rows.

Generates two analytical reports—a Base-100 indexed series and a date-by-category pivot table—from supplied transformation throughput records (processed_rows, duration_seconds) for up to 200 rows.

Generates two local analytical reports — a Base-100 indexed series and an equal-width histogram — for transformation throughput data (processed_rows or duration_seconds) supplied by the caller, across up to 200 rows.

Analyzes transformation throughput records (processed_rows, duration_seconds) producing a Base-100 indexed trend series and a keyed dataset comparison report for up to 200 rows.

Analyzes transformation throughput records to produce category frequency distributions and adjacent row change reports for processed_rows or duration_seconds fields.

Analyzes transformation throughput records by computing category frequencies for dataset_group and an equal-width histogram for either processed_rows or duration_seconds, returning two analytical reports for up to 200 rows.

Analyzes transformation throughput records to compute category frequencies for dataset_group and explicitly fills missing values in processed_rows or duration_seconds using zero, mean, or median strategies.

Analyzes transformation throughput records to compute category frequencies by dataset_group and flag IQR-based outliers for processed_rows or duration_seconds fields.

Analyzes transformation throughput records (processed_rows, duration_seconds) to produce category frequency distributions and a keyed comparison between two supplied datasets, using local analytical engines with no external lookups.

Computes daily sum time series and Base-100 index series for transformation throughput metrics (processed_rows, duration_seconds) from up to 200 supplied records.

Computes a daily sum time series and fills missing values for transformation throughput records (processed_rows, duration_seconds) across up to 200 rows.

Computes daily aggregated sums and IQR-based outlier flags for transformation throughput records (processed_rows, duration_seconds) across up to 200 rows, returning two analytical reports.

Computes a daily sum time series and a keyed dataset comparison for transformation throughput metrics (processed_rows, duration_seconds) across up to 200 supplied records.

Computes a daily sum time series and a secondary-measure weighted mean for transformation throughput records (processed_rows, duration_seconds) over up to 200 supplied rows.

Computes a daily sum time series and a trailing moving-average series for transformation throughput metrics (processed_rows or duration_seconds) from supplied records.

Computes a daily sum time series and a Pearson correlation between processed_rows and duration_seconds from user-supplied transformation throughput records (up to 200 rows).

Generates two analytical reports on transformation throughput records — a date-by-category pivot table and a keyed dataset comparison — using supplied processed_rows and duration_seconds data.

Analyzes user-supplied transformation throughput records to produce a duplicate key report and a Base-100 indexed series for processed_rows or duration_seconds metrics.

Analyzes transformation throughput records to produce a duplicate key report and a daily sum time series for processed_rows or duration_seconds, across up to 200 rows.

Analyzes transformation throughput records to produce a duplicate key report and an equal-width histogram for processed_rows or duration_seconds fields.

Analyzes supplied transformation throughput records to produce a duplicate key report and IQR-based outlier flags for processed_rows or duration_seconds fields, across up to 200 rows.

Generates two analytical reports — an equal-width histogram and a date-by-category pivot — over transformation throughput records (processed_rows, duration_seconds) for up to 200 supplied rows.

Generates an equal-width histogram and IQR-based outlier flags for transformation throughput data (processed_rows or duration_seconds) from up to 200 supplied records.

Computes an equal-width histogram and a keyed dataset comparison for up to 200 transformation throughput records (processed_rows and duration_seconds fields), returning two analytical reports per call.

Computes an equal-width histogram and a two-measure Pearson/Spearman correlation for supplied transformation throughput records (processed_rows, duration_seconds) — up to 200 rows, two reports per call.

Deduplicates transformation throughput records and computes an equal-width histogram over processed_rows or duration_seconds for up to 200 rows in a single API call.