All Services

Routes AI API calls through a pay-per-call marketplace gateway with OpenAI-compatible interface, settling payments in USDC on Base or Solana via x402 protocol.

Routes AI API calls through a smart gateway with OpenAI-compatible interface, pay-per-call billing settled in USDC on Base or Solana via x402 protocol

Routes AI API requests through a smart gateway marketplace, charging per call via x402 micropayments settled in USDC on Base or Solana

Routes an AI API call through the JarvisClaw marketplace gateway (endpoint #74), settled via x402 micropayments in USDC on Base or Solana, with OpenAI-compatible interface.

Fetches current ticker/price data for markets available on the JarvisClaw AI API marketplace

Retrieves AI-powered responses through a smart-routing marketplace gateway that bills per call via x402 micropayments settled in USDC

Routes AI API requests through a smart gateway with OpenAI-compatible interface, paid per-call in USDC via x402 protocol on Base or Solana

Routes an AI query through the JarvisClaw marketplace gateway (endpoint #802), settling payment per-call in USDC via x402 on Base or Solana, with OpenAI-compatible request/response format.

Routes AI API requests through a smart gateway marketplace, settling pay-per-call payments in USDC via x402 on Base or Solana, with OpenAI-compatible interface

Routes a query to an AI model through the JarvisClaw marketplace gateway (endpoint #106), billed per-call in USDC via x402 protocol on Base or Solana.

Routes a query to an AI model via JarvisClaw's smart-routing marketplace, billed per-call at $0.0575 USDC using the x402 payment protocol on Base or Solana.

Routes AI inference requests through a pay-per-call marketplace gateway (endpoint #119), settling micro-payments in USDC on Base or Solana via x402 protocol.

Retrieves or queries decentralized exchange (DEX) trade data via a pay-per-call AI API gateway settled in USDC

Retrieves a specific AI API marketplace listing (item #492) via smart-routed, OpenAI-compatible gateway with pay-per-call billing settled in USDC

Routes AI API requests through a smart gateway with pay-per-call pricing via x402, settling in USDC on Base or Solana, with OpenAI-compatible interface

Routes AI API requests through a pay-per-call marketplace gateway with smart routing, settling payments in USDC on Base or Solana via x402 protocol

Routes AI inference requests through a smart OpenAI-compatible gateway, billed per-call via x402 micropayments settled in USDC on Base or Solana.

Routes an AI query through JarvisClaw's OpenAI-compatible marketplace gateway, settling payment per call in USDC on Base or Solana via x402.

Routes a query to an AI model via a pay-per-call OpenAI-compatible gateway, settling payment in USDC on Base or Solana via x402.

Top up Jatevo AI account credits by specifying an amount and currency via the x402 payment protocol

Add credits to a Jatevo AI developer account by specifying an amount, currency, and account ID

Returns a structured playbook (slug, tier, sections) with actionable conversion strategies for local service businesses, authored by a Phoenix operator.

Validates that every cell in a job-execution CSV table does not exceed a specified character length, returning a per-cell audit report for up to 1000 rows.

Validates a CSV of job execution records and returns a report of rows that fail defined constraints (numeric bounds, cell length, allowed category values).

Validates that required cells in a job-execution CSV are non-empty, returning a structured check report for up to 1000 rows.

Validates a CSV of job execution import data and exports only the rows that pass all defined constraints, up to 1000 rows.

Computes a daily sum series and a secondary-measure weighted mean for supplied job listing inventory records (listing_count, duplicate_listings), returning two analytical reports for up to 200 rows.

Analyzes supplied job listing inventory records to produce a duplicate key report and a base-100 indexed series for listing_count or duplicate_listings, covering up to 200 rows.

Analyzes uploaded job listing inventory records to produce a duplicate key report and category frequency breakdown for up to 200 rows.

Runs two local analytical reports on supplied job listing inventory rows: a duplicate key report and a grouped numeric summary for listing_count or duplicate_listings.

Generates a duplicate key report and numeric row ordering for up to 200 job listing inventory records (listing_count, duplicate_listings) using local analytical engines.

Analyzes supplied job listing inventory records to produce a duplicate key report and a secondary-measure weighted mean, using local analytical engines on up to 200 rows.

Computes an equal-width histogram of listing_count (or duplicate_listings) and a weighted mean of the secondary measure for up to 200 job listing inventory rows in two independent analytical reports.

Analyzes supplied job listing inventory records to produce two analytical reports: exact row deduplication and adjacent row changes for listing_count or duplicate_listings fields.

Deduplicates exact rows and pivots job listing inventory data (listing_count or duplicate_listings) by date and category, producing two analytical reports from supplied data.

Deduplicates exact rows and computes numeric distribution statistics for job listing inventory records (listing_count, duplicate_listings) across up to 200 rows.

Deduplicates job listing inventory rows and computes correlation between listing_count and duplicate_listings across up to 200 supplied records, returning two analytical reports.

Runs two local analytical reports on job listing inventory data: a grouped numeric summary and a date-by-category pivot, across up to 200 rows.

Computes a grouped numeric summary and a secondary-measure weighted mean for supplied job listing inventory records (listing_count, duplicate_listings) across company groups and dates.

Computes numeric distribution statistics and adjacent row change analysis for job listing inventory data (listing_count, duplicate_listings) across up to 200 rows.

Computes numeric distribution statistics and numeric row ordering for up to 200 job listing inventory records across listing_count and duplicate_listings fields.

Filters job listing inventory rows by a numeric range and computes adjacent row changes for listing_count or duplicate_listings fields, returning two analytical reports for up to 200 rows.

Filters job listing inventory rows to a numeric interval and fills missing values using zero, mean, or median for listing_count or duplicate_listings fields.

Generates two analytical reports (numeric row ordering and Base-100 index series) for up to 200 supplied job listing inventory records across listing_count or duplicate_listings fields.

Computes numeric row ordering and a daily sum time series for job listing inventory data (listing_count, duplicate_listings) across up to 200 rows.

Generates two analytical reports (numeric row ordering and date-by-category pivot) for supplied job listing inventory data covering listing_count and duplicate_listings metrics.

Performs numeric row ordering and keyed dataset comparison on two supplied job listing inventory datasets (listing_count, duplicate_listings) for up to 200 rows each.

Sorts job listing inventory rows numerically and computes the correlation between listing_count and duplicate_listings for up to 200 supplied records, returning two analytical reports.

Runs two analytical reports (record quality audit and adjacent row changes) on up to 200 rows of job listing inventory data (listing_count, duplicate_listings) using local analytical engines.

Audits record quality and identifies exact duplicate rows in job listing inventory data (listing_count, duplicate_listings) for up to 200 rows, returning two independent analytical reports.

Runs three analytical reports on job listing inventory data: a record quality audit, exact row deduplication, and numeric distribution analysis for listing_count or duplicate_listings fields.

Audits record quality and fills missing values in job listing inventory data (listing_count, duplicate_listings) for up to 200 rows, returning two independent analytical reports.

Audits data quality and filters rows by numeric range for job listing inventory records containing listing_count and duplicate_listings fields, returning two analytical reports for up to 200 rows.

Runs three local analytical reports on job listing inventory data: record quality audit, string normalisation, and a date-by-category pivot, for up to 200 rows at $0.01 USDC.

Runs three local analytical reports (record quality audit, string normalisation, and numeric distribution) on up to 200 rows of job listing inventory data containing listing counts and duplicate listing counts.

Computes a secondary-measure weighted mean and performs a keyed dataset comparison on up to 200 rows of job listing inventory records (listing_count, duplicate_listings), returning two independent analytical reports.

Normalises strings and generates a duplicate key report for supplied job listing inventory records (listing_count, duplicate_listings) — up to 200 rows, two independent analytical reports per call.

Runs string normalisation and an equal-width histogram report on up to 200 job listing inventory records (listing_count, duplicate_listings) using local analytical engines.

Performs string normalisation and keyed dataset comparison on two sets of job listing inventory records (listing_count, duplicate_listings) for up to 200 rows each, returning 2 independent analytical reports.

Normalises string fields and filters job listing inventory rows by a numeric interval (min/max range) across listing_count or duplicate_listings, returning up to 2 analytical reports for up to 200 rows.

Normalises string fields and applies numeric row ordering to job listing inventory records (listing_count, duplicate_listings) for up to 200 rows, returning 2 analytical reports.

Performs string normalisation and secondary-measure weighted mean analysis on up to 200 rows of job listing inventory data (listing_count, duplicate_listings), returning 2 local analytical reports per call.

Normalises string fields and computes a trailing moving average series for job listing inventory data (listing_count, duplicate_listings) across up to 200 rows.

Computes Pearson/Spearman correlation between listing_count and duplicate_listings, and fills missing values in a chosen field using zero, mean, or median imputation — two independent analytical reports for up to 200 rows of job listing inventory data.

Searches live Bing web results to surface public job listings and hiring trend data specifically for the small business sector

Searches live public web pages for salary data, job postings, and hiring trends specifically relevant to AI agent builders, returning source links and text snippets.

Computes adjacent row-over-row changes and a base-100 indexed series for join coverage metrics (matched_rows or source_rows) across up to 200 supplied records.

Analyzes join coverage data (matched_rows and source_rows) to detect adjacent row changes and fill missing values using zero, mean, or median imputation — returning two analytical reports for up to 200 rows.

Analyzes join coverage data with two independent reports: sequential adjacent-row change detection and keyed dataset comparison, across up to 200 rows of matched_rows/source_rows data.

Analyzes join coverage records (matched_rows, source_rows) by computing category frequencies and performing a keyed dataset comparison between two supplied datasets of up to 200 rows each.

Analyzes join coverage records by computing category frequency distributions and Pearson/rank correlation between matched_rows and source_rows measures.

Computes two analytical reports (daily sum series and adjacent row changes) over supplied join coverage data (matched_rows and source_rows) for up to 200 rows.

Computes a daily sum series and a secondary-measure weighted mean for supplied join coverage records (matched_rows, source_rows) across up to 200 rows in two independent reports.

Computes a daily sum time series and two-measure correlation analysis for join coverage data (matched_rows vs source_rows) supplied by the caller, up to 200 rows.

Analyzes join coverage data rows to produce two reports: a duplicate key report and an adjacent row changes report, for up to 200 supplied rows.

Analyzes join coverage data (matched_rows, source_rows) to produce a duplicate key report and a Base-100 indexed series for up to 200 rows.

Analyzes join coverage records to produce a duplicate key report and a trailing mean time series for matched_rows or source_rows data.

Deduplicates supplied join coverage rows and computes a Base-100 indexed series for matched_rows or source_rows metrics across up to 200 records.

Performs exact row deduplication and category frequency analysis on up to 200 join coverage records (matched_rows, source_rows) for $0.01 USDC, returning two independent analytical reports.

Runs two analytical reports on join coverage data: exact row deduplication and a date-by-category pivot table, for up to 200 supplied rows.

Deduplicates up to 200 join coverage records by exact row and produces a duplicate key report across matched_rows and source_rows fields.

Deduplicates exact rows and fills missing values in join coverage data (matched_rows, source_rows), producing 2 analytical reports for up to 200 rows.

Deduplicates join coverage records and generates a grouped numeric summary report for matched_rows or source_rows metrics, processing up to 200 rows in two independent analytical reports.

Analyzes up to 200 join coverage records by performing exact row deduplication and numeric distribution reporting on matched_rows or source_rows fields.

Deduplicates exact rows and filters by numeric interval in supplied join coverage records (matched_rows, source_rows), returning two analytical reports for up to 200 rows.

Performs exact row deduplication and trailing mean series analysis on supplied join coverage records (matched_rows, source_rows) for up to 200 rows.

Deduplicates exact rows and computes correlation between matched_rows and source_rows measures for up to 200 join coverage records, delivering two analytical reports in a single call.

Analyzes join coverage records (matched_rows, source_rows) by computing a grouped numeric summary and applying a numeric interval filter, returning two analytical reports for up to 200 rows.

Computes grouped numeric summary statistics and numeric row ordering for join coverage data (matched_rows, source_rows) across up to 200 supplied records, returning two analytical reports.

Runs IQR-based outlier detection and two-measure Pearson/rank correlation on up to 200 join coverage records (matched_rows, source_rows), returning two independent analytical reports.

Compares two keyed datasets on matched_rows or source_rows metrics, filling explicit missing values and producing two analytical reports for up to 200 rows.

Generates two local analytical reports — a numeric distribution and a date-by-category pivot — for join coverage records containing matched_rows and source_rows fields, for up to 200 rows.

Computes a numeric distribution report and a grouped numeric summary for join coverage metrics (matched_rows, source_rows) across up to 200 supplied records.

Computes numeric distribution statistics and row ordering analysis for join coverage data (matched_rows, source_rows) across up to 200 supplied rows, returning two independent analytical reports.

Computes a numeric distribution report and a trailing mean time series for join coverage metrics (matched_rows, source_rows) across up to 200 supplied rows.

Analyzes join coverage records (matched_rows, source_rows) by applying a numeric interval filter and detecting adjacent row changes across up to 200 rows in two independent reports.

Filters join coverage rows (matched_rows or source_rows) by a numeric interval and produces a date-by-category pivot table, returning two analytical reports for up to 200 supplied rows.

Filters join coverage records (matched_rows, source_rows) to a numeric interval and fills missing values, returning two analytical reports for up to 200 rows.

Analyzes join coverage data by applying numeric interval filtering and comparing two keyed datasets (rows vs other) across matched_rows and source_rows metrics, returning 2 analytical reports for up to 200 rows.

Filters join coverage records by a numeric interval on a chosen measure and computes a secondary-measure weighted mean, returning two analytical reports for up to 200 rows.