All Services

Cleans and sanitizes written text content using AI, removing noise, formatting issues, or unwanted elements

Generates a short written snippet or excerpt based on a given title using AI-powered content drafting.

Audits written content using AI to identify issues and provide optimization recommendations.

Verifies a circular-economy skip/waste-diversion digital twin by validating its manifest hash against an on-ledger record and returning a certified passport with a Lean4 proof hash.

Returns NIST Test, Evaluation, Validation & Verification (TEVV) alignment data for AI systems, including framework details, comment periods, and dashboard metrics.

Classify up to 100 declared measurement intervals against tolerances as pass, fail, or hold using integer millimetre values and absolute interval half-widths.

Returns a renters insurance guide covering coverage amounts, carrier comparisons, and umbrella policy guidance

Returns a paid, LLM-generated decision procedure with cost and runtime thresholds for evaluating whether to adopt auto-generated API clients (Ballet-style integration writers) after initial vetting.

Searches the live web for official SDK integration examples and quickstarts tailored to research team use cases

Verifies an x402 payment quote before an AI agent pays, checking the asset, price, payee, and resource binding for safety.

Assesses the risk of a Base wallet address before an AI agent makes an x402 USDC payment, returning a risk score, risk level, and safe-to-proceed verdict.

Verifies an x402 payment quote before an AI agent pays, checking the Base USDC asset, price, payee, and resource binding for safety.

Computes daily sum time series and secondary-measure weighted mean for internal support records (responded_requests, received_requests) on up to 200 supplied rows.

Analyzes up to 200 internal support records to produce a duplicate key report and IQR-based outlier flags for responded_requests or received_requests fields.

Analyzes internal support records (responded_requests, received_requests) to produce a duplicate key report and numeric row ordering for up to 200 rows.

Deduplicates rows of internal support request records and filters them by a numeric interval on responded_requests or received_requests fields, returning up to 2 analytical reports for up to 200 rows.

Computes grouped numeric summaries and numeric row ordering for internal support records (responded_requests, received_requests) across up to 200 rows, producing two analytical reports per call.

Analyzes internal support request data (responded_requests, received_requests) by producing a numeric distribution report and an adjacent-row change report for up to 200 rows.

Generates a numeric distribution report and a base-100 indexed series for up to 200 rows of internal support request data (responded_requests or received_requests).

Filters internal support records by a numeric interval and pivots date data by category, producing two analytical reports for up to 200 rows.

Filters internal support records (responded_requests, received_requests) by a numeric interval and computes a secondary-measure weighted mean, returning up to 2 analytical reports for up to 200 rows.

Analyzes internal support ticket data (responded_requests, received_requests) to produce numeric row ordering and adjacent row change reports for up to 200 rows.

Computes numeric row ordering and trailing mean series for internal support records (responded_requests, received_requests) across up to 200 rows, returning 2 analytical reports.

Ranks support records by a chosen numeric field and computes the correlation between responded_requests and received_requests for up to 200 rows of internal support data.

Runs three analytical reports (record quality audit, string normalisation, and category frequencies) on up to 200 internal support records containing responded and received request counts.

Runs three offline analytical reports on internal support records: a data quality audit, string normalisation, and grouped numeric summary — up to 200 rows per call.

Runs three analytical reports on internal support records — record quality audit, string normalisation, and numeric distribution — for up to 200 rows of responded/received request data.

Runs three offline analytical reports on internal support records (responded_requests, received_requests): a record quality audit, string normalisation, and a secondary-measure weighted mean — up to 200 rows per call.

Runs two local analytical reports on internal support records: string normalisation of team/group labels and a date-by-category pivot for responded_requests or received_requests, up to 200 rows.

Normalises strings and flags IQR-based outliers in internal support records (responded_requests, received_requests) for up to 200 rows, producing 2 independent analytical reports.

Computes a trailing moving average series and a secondary-measure weighted mean for internal support ticket data (responded_requests and received_requests) over up to 200 rows.

Computes adjacent-row change analysis and a date-by-category pivot table for up to 200 interview transcript records containing word counts and audio duration metrics.

Analyzes interview transcript records to produce category frequency distributions and a keyed comparison between two supplied datasets, up to 200 rows each.

Deduplicates exact duplicate rows and fills missing values in interview transcript datasets (transcript_words, audio_minutes), returning two analytical reports for up to 200 rows.

Deduplicates and numerically orders rows in supplied interview transcript datasets (transcript_words, audio_minutes) and produces two analytical reports.

Deduplicates interview transcript rows and computes a trailing mean series for transcript_words or audio_minutes across up to 200 supplied records.

Computes grouped numeric summaries and a secondary-measure weighted mean for interview transcript records (transcript_words, audio_minutes) across up to 200 rows, returning two independent analytical reports.

Computes numeric distribution statistics and grouped numeric summaries for interview transcript data (transcript word counts and audio minutes) across up to 200 rows.

Computes numeric distribution statistics and a secondary-measure weighted mean for interview transcript records (transcript_words, audio_minutes) across up to 200 rows, returning two analytical reports.

Assigns sequential numeric row order and generates a Base-100 index series for up to 200 interview transcript records (transcript_words, audio_minutes), returning two analytical reports.

Runs two analytical reports on interview transcript data: a record quality audit and a date-by-category pivot, for up to 200 rows.

Runs three local analytical reports on interview transcript data: a record quality audit, exact row deduplication, and a grouped numeric summary of transcript_words or audio_minutes across up to 200 rows.

Audits data quality, normalises strings, and computes correlation between transcript_words and audio_minutes for up to 200 interview transcript records in a single batch call.

Computes a secondary-measure weighted mean and a date-by-category pivot table for up to 200 interview transcript records containing word counts and audio durations.

Performs string normalisation and Base-100 indexing analysis on up to 200 rows of interview transcript data (transcript_words and audio_minutes), returning two analytical reports.

Normalises string fields and produces a date-by-category pivot table for up to 200 interview transcript records (transcript_words, audio_minutes).

Normalises strings and performs keyed dataset comparison on two sets of interview transcript records (transcript_words, audio_minutes), returning 2 analytical reports for up to 200 rows each.

Normalises transcript_words strings and computes correlation between transcript_words and audio_minutes across up to 200 interview transcript rows, returning two independent analytical reports.

Computes a trailing mean time series and a date-by-category pivot table for supplied interview transcript records (transcript_words, audio_minutes).

Generates two analytical reports (a Base-100 index series and a date-by-category pivot table) from supplied inventory administration data covering count_sessions and discrepancy_count metrics.

Computes a Base-100 index series and a secondary-measure weighted mean for inventory administration records (count_sessions, discrepancy_count) over up to 200 rows using local analytical engines.

Computes category frequency counts and filters records by a numeric interval for inventory administration data (count_sessions, discrepancy_count) across up to 200 rows.

Computes category frequency distributions and a secondary-measure weighted mean for up to 200 inventory administration records (count_sessions, discrepancy_count).

Generates two local analytical reports (duplicate key detection and category frequency counts) for up to 200 inventory administration rows containing session count and discrepancy metrics.

Runs two local analytical reports on supplied inventory administration data: a duplicate key report and a date-by-category pivot, for up to 200 rows.

Runs two local analytical reports on supplied inventory administration data: a duplicate key detection report and a numeric interval filter, across up to 200 rows.

Generates a duplicate key report and a trailing mean series for inventory administration data (count_sessions, discrepancy_count) across up to 200 rows using local analytical engines.

Computes an equal-width histogram and fills missing values for up to 200 inventory administration rows containing session count and discrepancy count fields, returning two local analytical reports.

Deduplicates inventory administration records and generates an equal-width histogram for count_sessions or discrepancy_count fields across up to 200 rows.

Computes a grouped numeric summary and a trailing moving-average series for inventory administration session and discrepancy data across up to 200 rows.

Filters inventory session/discrepancy rows by a numeric range and computes adjacent-row (period-over-period) changes, returning two analytical reports for up to 200 rows.

Filters inventory administration rows by a numeric interval and computes a daily sum time series for session counts or discrepancy counts across up to 200 rows.

Filters inventory administration rows by a numeric interval on a chosen field and computes the correlation between count_sessions and discrepancy_count for up to 200 supplied rows.

Sorts inventory administration rows by a chosen numeric field and generates an equal-width histogram for up to 200 records covering count_sessions or discrepancy_count.

Audits record quality and computes adjacent row changes for inventory administration data (count_sessions, discrepancy_count) across up to 200 rows, returning two analytical reports.

Runs two local analytical reports on supplied inventory session data: a record quality audit and a date-by-category pivot, for up to 200 rows.

Runs three local analytical reports on inventory administration rows: record quality audit, exact row deduplication, and numeric row ordering for count_sessions or discrepancy_count fields.

Runs three local analytical reports on inventory session data: record quality audit, string normalization, and exact row deduplication for up to 200 rows.

Computes a secondary-measure weighted mean and a date-by-category pivot table for supplied inventory administration records (count_sessions, discrepancy_count) across up to 200 rows.

Computes Pearson correlation between count_sessions and discrepancy_count, and fills missing values using zero, mean, or median for up to 200 inventory administration rows.

Rebases inventory count shortfall data (expected vs. counted units) to a Base-100 index, anchored to a chosen reference row, for up to 200 retail records.

Calculates the inventory count shortfall by comparing counted units against expected units for a single retail record.

Calculates the gap between expected and counted inventory units relative to a specified target, returning a bounded shortfall report for up to 200 retail records.

Classifies inventory count shortfall values (expected minus counted units) into threshold-based categories for up to 200 retail records.

Reads a value from a JSON document by traversing a dot-separated path, tailored for inventory workflows.

Calculates adjacent period-over-period changes in inventory position metrics (on-hand, on-order, backorders) for retail scenario analysis.

Computes a base-100 indexed rebase report for inventory position data (on-hand, on-order, backorders) across multiple time periods or SKUs, enabling local scenario analysis and trend normalization.

Calculates period-over-period changes in inventory sell-through rate across adjacent time periods from supplied retail figures.

Calculates and summarizes the distribution of inventory sell-through rates from supplied sold and ending unit figures across multiple rows.

Searches live public web pages for information about inventory sync platforms, returning source links and snippets tailored for analysts.

Searches live public web pages for information about inventory synchronization platforms targeted at technology buyers, returning source links and snippets.

Analyzes a Base wallet address for on-chain buyer behavior OR audits an x402 resource URL/domain for discoverability position, crawl depth, and ranking levers within the CDP discovery catalog.

Compares two sets of invoice ageing records by row key and fills missing values in outstanding_amount or age_days fields, producing two analytical reports for up to 200 rows.

Sorts invoice ageing records by a numeric field and fills missing values using zero, mean, or median imputation, returning two analytical reports for up to 200 rows.

Runs three local analytical reports on invoice ageing data: a record quality audit, string normalisation, and numeric row ordering by outstanding_amount or age_days — up to 200 rows per call.

Normalises string fields and orders rows numerically for invoice ageing records containing outstanding_amount and age_days, producing 2 analytical reports for up to 200 rows.

Audits a target URL or domain for safety, structured data presence, and geographic risk scoring in real time

Adds 5,000,000 Swarmio tokens ($5.00 worth) to the authenticated ioswarm.io account balance for use across all API run modes.

Performs a technical and professional digital audit of a specified domain hostname

Audits up to 200 labelled issue-kind text records to identify exact normalised duplicates within the dataset.

Splits up to 200 labelled issue-classification text records (bug/request/question/other) into grouped train/test partitions and returns local dataset split deliverables with naive-Bayes baselines.

Exports up to 200 labelled issue-classification records (bug/request/question/other) as a JSONL dataset for local ML evaluation and naive-Bayes baselines.

Returns a low-confidence review queue for a naive-Bayes issue-kind classifier, flagging up to 200 labelled text records where the model's predictions are uncertain.

Computes top-k label coverage metrics for a naive-Bayes issue-kind classifier (bug/request/question/other) given up to 200 labelled text records with predicted probabilities.

Detects text overlap between training and evaluation sets for issue-kind classification (bug/request/question/other) using a local naive-Bayes baseline.

Deduplicates exact rows and reports duplicate keys in issue throughput records (issues_opened, issues_closed) for up to 200 rows, producing two independent analytical reports.

Deduplicates and numerically orders up to 200 rows of issue throughput records (issues_opened, issues_closed) and produces 2 analytical reports per call.

Filters issue throughput records (issues_opened/issues_closed) by a numeric interval and computes adjacent-row changes, returning two bundled analytical reports for up to 200 rows.

Ranks issue throughput rows numerically and compares two keyed datasets of issues_opened/issues_closed data, returning two analytical reports for up to 200 rows.

Runs two local analytical reports on issue throughput data: a record quality audit and an adjacent row changes analysis, for up to 200 rows of issues_opened/issues_closed data.