All Services

Runs three local analytical reports (record quality audit, string normalisation, and numeric distribution) on up to 200 registry snapshot rows containing registered_entities and changed_entities fields.

Runs three analytical reports (record quality audit, string normalisation, and two-measure correlation) on registry snapshot data containing registered_entities and changed_entities fields, for up to 200 rows.

Runs two analytical reports on registry snapshot data: a data quality audit and a trailing mean time series, for up to 200 rows of registered/changed entity counts.

Computes a weighted mean of a selected secondary measure and a date-by-category pivot table from up to 200 registry snapshot rows containing registered_entities and changed_entities counts.

Computes a secondary-measure weighted mean and performs keyed dataset comparison on two supplied registry snapshot datasets (registered_entities, changed_entities) of up to 200 rows each.

Analyzes registry snapshot data by normalizing company group strings and computing adjacent row changes for registered_entities or changed_entities fields, returning 2 analytical reports for up to 200 rows.

Performs string normalisation and Base-100 index series computation on up to 200 rows of registry snapshot data covering registered_entities and changed_entities fields.

Performs string normalisation and category frequency analysis on up to 200 registry snapshot rows containing registered and changed entity counts, returning two analytical reports.

Runs two local analytical reports (string normalisation and daily sum series) on up to 200 rows of registry snapshot data containing registered and changed entity counts.

Normalises strings and deduplicates exact rows in registry snapshot records (registered_entities, changed_entities) for up to 200 rows, returning 2 independent analytical reports.

Normalises company group strings and produces grouped numeric summaries for registry snapshot records (registered_entities, changed_entities) across up to 200 rows.

Normalises string fields and flags IQR-based outliers in registry snapshot data (registered_entities, changed_entities) for up to 200 rows, producing two independent analytical reports.

Runs string normalisation and numeric distribution analysis on registry snapshot data (registered_entities, changed_entities) for up to 200 rows, producing two independent analytical reports.

Normalises company_group strings and filters registry snapshot rows (registered_entities, changed_entities) to a specified numeric interval, returning up to 2 analytical reports for up to 200 rows.

Computes trailing moving-average series and adjacent-row delta series for up to 200 registry snapshot rows across two metrics (registered_entities, changed_entities) in a single call.

Computes a trailing moving-average time series and a base-100 indexed series for registry snapshot data (registered_entities, changed_entities) supplied by the caller.

Computes a rolling trailing mean time series and fills missing values in registry snapshot data (registered_entities, changed_entities) using a chosen fill method.

Computes trailing moving-average time series and IQR-based outlier flags for registry snapshot data (registered_entities and changed_entities fields) across up to 200 rows, producing two independent analytical reports.

Computes trailing mean time series and performs keyed dataset comparison on registry snapshot data (registered_entities, changed_entities) for up to 200 rows across two independent analytical reports.

Computes a trailing mean time series and a secondary-measure weighted mean for supplied registry snapshot records covering registered and changed entities.

Computes a trailing moving average series and a two-measure correlation report for supplied registry snapshot data (registered_entities, changed_entities) on up to 200 rows.

Computes Pearson correlation between registered_entities and changed_entities in registry snapshot data, while filling missing values using zero, mean, or median imputation, for up to 200 rows.

Computes two analytical reports — a correlation between registered_entities and changed_entities, plus a keyed comparison across two supplied datasets — on registry snapshot records for up to 200 rows.

Fetches recent news articles about regulation, legislation, and government policy relevant to product teams, via live Google News RSS results.

Fetches recent Google News RSS results about regulation, legislation, and government policy, curated for research team workflows.

Searches live web sources to find primary-source regulatory records, filings, and enforcement notices relevant to integration developers.

Searches live web sources to find primary-source regulator records, notices, and filings relevant to product teams.

Searches live DuckDuckGo results for public regulatory guidance and official regulatory references relevant to the consulting industry.

Searches live DuckDuckGo results to find official regulatory guidance and public references specific to procurement topics

Searches live DuckDuckGo results for public regulatory guidance and official regulatory references relevant to product teams

Searches live DuckDuckGo results to surface public regulatory guidance and official regulatory references tailored for research team use cases.

Computes period-over-period changes in rejected share fraction for cryptocurrency mining operations across a sequence of time periods.

Calculates the rejected share fraction (rejected/total shares ratio) for up to 200 mining rows in a single batch request.

Computes and compares the rejected share fraction metric for cryptocurrency mining operations between two time periods (before and after).

Computes the benchmark correlation of rejected share fraction values across mining datasets, comparing against user-supplied benchmark series.

Computes a distribution histogram of rejected share fractions from supplied mining share data across a configurable number of bins.

Detects IQR-based statistical outliers in mining rejected share fraction data across a batch of rows

Computes the local finite-change elasticity of the rejected share fraction metric for cryptocurrency mining, given a user-supplied baseline and a percentage step size.

Performs ordered trend analysis on a time-series of rejected share fractions in cryptocurrency mining, returning a bounded statistical trend report.

Ranks up to 200 mining records by rejected share fraction (rejected_shares / total_shares), returning an ordered report with computed values.

Calculates the rejected share fraction (ratio of rejected to total shares) for a given set of mining parameters in a single bounded computation.

Classifies whether the rejected share fraction from mining data falls within a specified threshold range, returning a bounded classification report.

Lists available Rekt CEO meme templates from the Brandify catalog, with optional filtering by query, category, and pagination

Submit a Like, Dislike, or Neutral rating for a completed meme brandification session

Retrieves a Relay SAT (Structured Attestation/Transaction) record by its unique ID, requiring a micropayment of $0.01 USDC on Base.

Looks up an email address against an identity graph to find correlated phone numbers, domains, and other linked identifiers

Assesses the risk level of a target domain by returning a risk score, probability tier, and threat signals

Scans a domain for non-human identity (NHI) credential exposures such as leaked API keys, tokens, or service account secrets

Generates a fixed-holdout learning curve for a labelled dataset of release change text records (feature, fix, documentation, maintenance) using a local naive-Bayes classifier.

Runs a grouped three-fold cross-validation using a naive-Bayes classifier on up to 200 labelled release change records to evaluate text classification accuracy across feature, fix, documentation, and maintenance categories.

Audits classifier labels and predictions for software release change type classification (feature, fix, documentation, maintenance) across up to 200 text records.

Computes the label distribution (class balance) of up to 200 labelled release-change text records across feature, fix, documentation, and maintenance categories.

Exports up to 200 labelled text records for release change classification (feature/fix/documentation/maintenance) as a JSONL file for local ML evaluation and naive-Bayes baseline training.

Identifies and surfaces low-confidence classifier predictions from a naive-Bayes release-change text classifier across up to 200 labeled records for human review.

Computes macro, micro, and weighted aggregate classification scores for a batch of labelled release-change text records across four categories (feature, fix, documentation, maintenance).

Computes the multiclass Brier score for a release-change classifier (feature/fix/documentation/maintenance) given up to 200 labelled text records with predicted probabilities.

Computes multiclass log loss metric for release-change text classification (feature/fix/documentation/maintenance) given labeled records with predicted probabilities.

Computes per-label precision and recall metrics for a naive-Bayes release-change classifier across up to 200 labelled text records with four categories: feature, fix, documentation, maintenance.

Trains a local naive Bayes text classifier on up to 200 labelled release-change records and classifies query texts into feature, fix, documentation, or maintenance categories.

Extracts action-marker lines (e.g. TODO items with dates) from release notes written in Markdown or plain text

Splits release notes markdown or plain text into bounded text chunks of a specified maximum character length using deterministic document processing.

Scans release notes Markdown or plain text for duplicate paragraphs and returns a bounded audit report identifying repeated content.

Masks email addresses and phone numbers in release notes Markdown or plain text using deterministic pattern matching, returning sanitized output suitable for public distribution.

Audits the heading hierarchy of release notes Markdown or plain text for structural correctness and consistency

Extracts and returns a structured heading outline from a release notes Markdown or plain text document

Extracts and inventories all HTTP links found within release notes Markdown or plain text documents

Scans release notes Markdown or plain text and inventories all ISO-date patterns found within the document

Analyzes the length and paragraph structure of release notes text, returning a deterministic profile report.

Extracts and inventories quoted passages from release notes documents supplied as Markdown or plain text

Reorders the recognised sections of a release notes document (e.g. Added, Changed, Fixed) into a canonical sequence using deterministic processing.

Audits a release notes document (Markdown or plain text) to verify all required sections are present and properly structured.

Extracts and isolates a specific section from a release notes document supplied as Markdown or plain text.

Applies a structured section template to supplied release notes content (Markdown or plain text), returning a consistently formatted release notes document.

Generates a link map from a web page URL, extracting all hyperlinks and their relationships for AI agent navigation and analysis.

Extracts structured table data from web content and returns reliable, schema-validated JSON for AI agents

Checks whether a given URL's CORS headers allow cross-origin requests from browsers or agents

Checks the TLS/SSL certificate validity and security of a given URL for use in JSON-reliability pipelines for AI agents.

Compares two OpenAPI specifications and returns a structured diff of their differences

Returns metadata about the Reliable JSON service for AI agents, including available endpoints, pricing, and capabilities.

Checks and enforces enterprise-configured spend limits for agent-to-agent payments, returning an approval disposition with an audit trail receipt

Approves, limits, and traces agent-to-agent payments with dual-control verification across enterprise rails

Reconciles and approves agent-to-agent payment invoices with dual-control verification and an auditable remittance trail

Approves, limits, and traces agent-to-agent payments across payment rails, returning a remittance receipt and dual-control verification status for enterprise workflows.

Verifies and approves a payment beneficiary for agent-to-agent remittance, returning an approval disposition and dual-control audit trail receipt.

Processes a flat record set through three sequential steps: deduplication, value-based row filtering, and grouped value counting — returning output and row counts per step.

Processes a batch of records through three sequential steps: deduplication, filtering rows with a value in a specified field, and computing a numeric summary — returning processed output and row counts per step.

Removes duplicate rows from a record set, filters rows where a specified text column matches a query string, then counts remaining records grouped by value.

Processes customer-supplied records by deduplicating rows, filtering by text match in a specified column, then returning a numeric summary with row counts per step.

Processes tabular records by sequentially removing duplicate rows, filtering rows where a text column matches a query, and sorting the results by a numeric column in descending order.

Computes adjacent row changes and a base-100 index series for render job metrics (render_seconds, sample_count) across up to 200 supplied rows.

Runs two analytical reports on render job data: adjacent row change analysis and a date-by-category pivot table for render_seconds or sample_count metrics.

Analyzes render job records by computing adjacent row changes and an equal-width histogram for render_seconds or sample_count fields, returning two analytical reports.

Analyzes up to 200 render job records for adjacent row changes and IQR-based outlier flags across render_seconds and sample_count fields, returning two independent analytical reports.

Computes adjacent row changes and secondary-measure weighted mean statistics for up to 200 render job records (render_seconds, sample_count), returning two analytical reports.

Analyzes render job records by computing adjacent row changes and two-measure correlation between render_seconds and sample_count for up to 200 rows.

Generates a Base-100 index series and a date-by-category pivot table from supplied render job records (render_seconds, sample_count) for up to 200 rows.

Computes a Base-100 indexed time series and a keyed dataset comparison for render job records (render_seconds, sample_count) across up to 200 rows.

Computes a Base-100 indexed time series and a two-measure correlation report for render job records (render_seconds, sample_count) supplied by the caller — up to 200 rows, no external lookups.

Analyzes render job records to produce category frequency distributions and a base-100 indexed time series for render_seconds or sample_count, across up to 200 rows.

Analyzes render job records to produce category frequency distributions and a keyed comparison between two supplied datasets (up to 200 rows each).