All Services

Normalises string fields and flags IQR-based outliers in endpoint telemetry records containing agent_count and reporting_agents metrics, returning two analytical reports for up to 200 rows.

Normalises string fields and filters rows by a numeric interval for up to 200 endpoint telemetry records (agent_count, reporting_agents) in two local analytical reports.

Compares two snapshots of ephemeris records to isolate true insertions and deletions from shared-record reordering across target, centre, frame, time-scale, correction, and kernel-pinned dimensions.

Checks which required fields are present or missing in supplied ephemeris snapshot records (target, centre, frame, time-scale, correction, kernel pins, etc.) without independently certifying their validity.

Sorts equipment maintenance records by row order and fills missing values in maintenance_hours or downtime_hours using zero, mean, or median imputation, returning 2 analytical reports for up to 200 rows.

Deduplicates error budget rows and filters records by a numeric interval (min/max) on failed_requests or total_requests, returning up to 2 analytical reports for up to 200 rows.

Deduplicates and numerically orders up to 200 rows of error budget data (failed_requests, total_requests) and produces 2 analytical reports per call.

Performs string normalisation and two-measure correlation analysis on error budget records (failed_requests, total_requests) for up to 200 rows, returning two independent analytical reports.

Analyzes event coverage session data by computing numeric row ordering and adjacent row changes for up to 200 supplied rows across two independent analytical reports.

Runs two analytical reports on event coverage data: a record quality audit and a secondary-measure weighted mean, processing up to 200 rows of covered/planned session data locally.

Runs string normalisation and trailing mean series analysis on event coverage data (covered_sessions, planned_sessions) for up to 200 rows, returning two analytical reports.

Normalises strings and computes correlation between covered_sessions and planned_sessions for up to 200 event coverage rows, producing two analytical reports.

Analyzes up to 200 exchange quote rows (bid_price/ask_price) to produce a duplicate key report and numeric row ordering, using local analytical engines with no external lookups.

Analyzes exchange quote records (bid/ask prices) by sorting rows numerically and comparing two keyed datasets, producing two analytical reports for up to 200 rows.

Audits data quality, normalises strings, and orders rows numerically for up to 200 exchange quote observation records containing bid and ask prices.

Routes HTTP POST RPC calls to backend services via a metered gateway, consuming from a pre-purchased bundle of 1000 requests

Computes local finite-change elasticity for expected-versus-received payout variance given retail figures, returning a bounded sensitivity report.

Deduplicates exact duplicate rows and applies numeric ordering to up to 200 expense claim records (claimed_amount, approved_amount), returning 2 analytical reports.

Generates a duplicate key report and a two-measure Pearson/rank correlation analysis for expense records containing submitted_amount and approved_amount fields, using local analytical engines on up to 200 rows.

Deduplicates expense rows and sorts them numerically by submitted_amount or approved_amount, returning two analytical reports for up to 200 rows.

Applies numeric row ordering and base-100 index series analysis to up to 200 expense records (submitted_amount, approved_amount), returning two local analytical reports per call.

Ranks expense rows numerically and computes a trailing mean series for submitted_amount or approved_amount fields across up to 200 expense records.

Runs three local analytical reports on experiment run timing data: a record quality audit, string normalisation, and numeric interval filter for run_seconds or sample_count fields.

Normalises numeric experiment signal records (up to 200 rows) across conditions and dates, returning a bounded string normalisation report for local descriptive analytics.

Audits a target domain hostname and returns a structured audit report via the Expertlawforum platform

Computes adjacent row-to-row changes and a secondary-measure weighted mean for up to 200 export validation records (valid_rows, exported_rows) in two independent local analytical reports.

Computes a Base-100 index series and a secondary-measure weighted mean for export validation records containing valid_rows and exported_rows fields, using local analytical engines with no external lookups.

Computes category frequency counts and Pearson/rank correlation between valid_rows and exported_rows for up to 200 export validation records, returning two analytical reports.

Analyzes up to 200 export validation rows to produce two reports: a duplicate key detection report and a numeric interval filter for valid_rows or exported_rows fields.

Runs two local analytical reports on export validation data: exact row deduplication and equal-width histogram distribution for valid_rows or exported_rows fields.

Runs two local analytical reports on export validation data: a grouped numeric summary and a numeric row ordering, over up to 200 rows of valid_rows/exported_rows data.

Sorts export validation records numerically by row and fills missing values in valid_rows or exported_rows using zero, mean, or median imputation, returning two analytical reports for up to 200 rows.

Validates export records by computing numeric row ordering and trailing mean series for valid_rows and exported_rows fields across up to 200 rows, returning two analytical reports.

Audits export validation records for quality issues and produces a grouped numeric summary of valid_rows or exported_rows fields, for up to 200 rows in two independent analytical reports.

Runs three local analytical reports on export validation row data: a record quality audit, string normalisation of dataset group labels, and a numeric interval filter on valid_rows or exported_rows fields.

Runs three local analytical reports on export validation row data: record quality audit, string normalisation, and secondary-measure weighted mean for up to 200 rows of valid_rows/exported_rows data.

Runs two local analytical reports (string normalisation and daily sum series) on up to 200 export validation records containing valid_rows and exported_rows fields.

Runs two local analytical reports on export validation data: string normalisation of a chosen metric field and a date-by-category pivot, for up to 200 rows.

Downloads the FABA AirMeter v1 software package or plugin for air metering functionality within the FABA agent ecosystem

Analyzes up to 200 facilities usage records to produce a duplicate key report and numerically ordered row ranking for occupied_seats or available_seats fields.

Ranks facilities usage rows numerically by occupied_seats or available_seats and computes a secondary-measure weighted mean across up to 200 supplied records, delivering two analytical reports in one call.

Normalises strings and compares two facilities usage datasets (occupied_seats, available_seats) by key, returning 2 analytical reports for up to 200 rows each.

Normalises team_group strings and filters facilities usage records (occupied_seats, available_seats) by a numeric min/max interval, producing up to 2 analytical reports for up to 200 rows.

Computes category frequency counts and numeric row ordering for up to 200 fact-check workflow records across claims_reviewed and references_collected fields.

Analyzes fact-check workflow records to produce a duplicate key report and numeric distribution for claims_reviewed or references_collected fields (up to 200 rows).

Deduplicates fact-check workflow records and computes a secondary-measure weighted mean across claims_reviewed and references_collected data, returning two analytical reports.

Computes grouped numeric summaries and numeric row ordering for fact-check workflow records (claims_reviewed, references_collected) across up to 200 rows.

Computes numeric distribution statistics and a daily sum time series for fact-check workflow data (claims reviewed and references collected) across up to 200 rows.

Sorts fact-check workflow records by a numeric field and computes a secondary-measure weighted mean, producing two analytical reports for up to 200 rows.

Runs two local analytical reports on fact-check workflow data: numeric row ordering and a trailing moving-average series for claims_reviewed or references_collected, across up to 200 rows.

Audits fact-check workflow records for data quality and ranks rows numerically by claims_reviewed or references_collected, returning two analytical reports for up to 200 rows.

Runs two local analytical reports on fact-check workflow data: a record quality audit and a secondary-measure weighted mean, across up to 200 rows of claims_reviewed and references_collected data.

Computes a secondary-measure weighted mean and performs keyed dataset comparison on up to 200 fact-check workflow records (claims_reviewed, references_collected), returning 2 analytical reports.

Performs string normalisation and base-100 index series computation on fact-check workflow records (claims reviewed, references collected) for up to 200 rows, producing 2 analytical reports.

Runs two local analytical reports on fact-check workflow data: string normalisation of channel groups and a daily sum time series for claims_reviewed or references_collected, for up to 200 rows.

Normalises strings and fills missing values in fact-check workflow records (claims_reviewed, references_collected) for up to 200 rows, returning 2 analytical reports.

Normalises string fields and filters rows by a numeric interval for fact-check workflow records containing claims_reviewed and references_collected, returning up to 2 analytical reports for up to 200 rows.

Normalises string fields and applies numeric row ordering to fact-check workflow records (claims_reviewed, references_collected) for up to 200 rows, returning 2 analytical reports.

Computes mathematical derivatives (calculus) via a self-hosted inference endpoint, pay-per-call with crypto.

Provides access to a broad marketplace of self-hosted AI and utility endpoints including chat, OCR, embeddings, translation, image editing, speech, and financial/math calculators, priced per call via crypto.

Fetches Total Value Locked (TVL) data across DeFi blockchain chains via a self-hosted proxy endpoint.

Fetches Bitcoin network statistics and blockchain data via a self-hosted utility endpoint, paid per call with crypto.

Returns the Total Value Locked (TVL) data for a specified DeFi protocol by name

Computes numeric row ordering and daily sum series reports for feature availability data (populated_features, expected_features) across up to 200 rows using local analytical engines.

Runs two local analytical reports on feature availability data: numeric row ordering and keyed dataset comparison across up to 200 rows of populated_features and expected_features.

Runs three offline analytical reports (record quality audit, string normalisation, and date-by-category pivot) on up to 200 feature-availability rows containing populated_features and expected_features counts.

Runs three independent analytical reports (record quality audit, string normalisation, and duplicate key detection) on supplied feature availability records (populated_features vs expected_features) for up to 200 rows.

Runs three analytical reports on feature availability records: a record quality audit, string normalisation, and a keyed dataset comparison between two supplied datasets (up to 200 rows each).

Runs three local analytical reports on feature availability records: a record quality audit, string normalisation, and numeric row ordering — up to 200 rows per call.

Normalises string values and orders rows numerically for feature availability records (populated_features, expected_features) across up to 200 rows, producing 2 independent analytical reports.

Deduplicates feed observation rows exactly and filters rows by a numeric interval on item_count or duplicate_items, returning two analytical reports for up to 200 rows.

Deduplicates feed observation rows exactly and computes correlation between item_count and duplicate_items across up to 200 submitted records, returning two analytical reports.

Provides stateful security monitoring for remote MCP (Model Context Protocol) endpoints, tracking and evidencing changes via a chat-completion-style API with per-call micropayments.

Executes stateful agent tasks via a remote MCP endpoint, tracking change evidence for security monitoring purposes, payable per call with x402 Base USDC.

Generates a structured research brief about a money bot, cryptocurrency, or financial entity via a pay-per-call MCP endpoint

A pay-per-call MCP proxy tool named 'Signal Sprint Base Block' hosted on fiatdock.com, forwarding JSON-RPC 2.0 requests to a seller's MCP endpoint for $0.005 USDC per call.

Generates two analytical reports (Base-100 indexed series and keyed dataset comparison) for field survey coverage records containing surveyed_m2 and target_m2 values, up to 200 rows.

Analyzes field survey coverage records (surveyed_m2, target_m2) to produce category frequency counts and numeric row ordering reports for up to 200 rows.

Computes a daily sum time series and a two-measure correlation report for field survey coverage data (surveyed_m2 vs target_m2) supplied by the caller, up to 200 rows.

Deduplicates field survey coverage records and produces grouped numeric summaries for surveyed_m2 or target_m2 across up to 200 rows.

Deduplicates and numerically orders field survey coverage records (surveyed_m2, target_m2) for up to 200 rows, returning 2 analytical reports.

Computes numeric distribution statistics and two-measure correlation for field survey coverage data (surveyed_m2 vs target_m2) on up to 200 supplied rows.

Filters field survey coverage rows by a numeric interval on a chosen measure and computes Pearson correlation between surveyed_m2 and target_m2 for up to 200 supplied rows.

Analyzes field survey coverage records by computing numeric row ordering and adjacent row changes for up to 200 rows of surveyed_m2 or target_m2 data.

Computes numeric row ordering and a base-100 index series for field survey coverage records (surveyed_m2 and target_m2), returning two analytical reports for up to 200 rows.

Computes numeric row ordering and secondary-measure weighted mean for field survey coverage records (surveyed_m2, target_m2) across up to 200 rows, returning 2 analytical reports.

Audits record quality and detects adjacent row changes in field survey coverage data (surveyed_m2, target_m2) for up to 200 rows, returning 2 independent analytical reports.

Audits record quality and applies numeric row ordering to field survey coverage data (surveyed_m2, target_m2) for up to 200 rows, producing 2 analytical reports.

Audits field survey coverage records for quality issues, normalises strings, and fills missing values in surveyed_m2 or target_m2 fields across up to 200 rows, returning 3 independent analytical reports.

Runs three local analytical reports on field survey coverage data: a record quality audit, string normalisation, and a trailing mean time series — all without external lookups or predictions.

Normalises station group strings and produces a date-by-category pivot table from field survey coverage records (surveyed_m2, target_m2) — two analytical reports for up to 200 rows.

Computes string normalisation and an equal-width histogram for field survey coverage records (surveyed_m2 and target_m2) across up to 200 rows.

Runs string normalisation and numeric distribution analysis on up to 200 field survey coverage records (surveyed_m2 and target_m2 fields), returning two analytical reports.

Normalises string fields and computes a secondary-measure weighted mean for up to 200 field survey coverage records (surveyed_m2, target_m2), returning two analytical reports.

Computes Pearson correlation between surveyed_m2 and target_m2, plus a weighted mean of the secondary measure, for up to 200 field survey coverage records.

Computes a daily sum time series and a secondary-measure weighted mean for up to 200 rows of financial statement data (revenue_amount, expense_amount).

Runs two local analytical reports on financial statement rows: a record quality audit and adjacent row change detection for revenue and expense amounts.

Computes a secondary-measure weighted mean and a date-by-category pivot table for up to 200 financial statement input rows (revenue_amount, expense_amount) using local analytical engines.

Analyzes firewall rule review records to produce category frequency counts and numeric row ordering reports for rules_reviewed or rules_removed fields, up to 200 rows.

Deduplicates firewall rule review records and computes a two-measure correlation between rules_reviewed and rules_removed for up to 200 rows, returning two analytical reports.