GG402 · Conversational ETL pipeline

Transform and process data through natural language conversation, applying ETL steps iteratively with full history tracking.

What it does

Transform and process data through natural language conversation, applying ETL steps iteratively with full history tracking.

  • Clean and transform datasets using plain English instructions
  • Build iterative data pipelines with conversational step tracking
  • Normalize unstructured data into structured formats
  • Validate data quality through interactive ETL workflows

Ideal buyer

Data engineers and AI agents needing flexible, code-free ETL transformations for ad-hoc data processing tasks.

Use with AXON

Run this through your governed agent wallet.

  1. 01
    Bootstrap AXON once with npx @axon402/init.
  2. 02
    Use the AXON runtime MCP tools to search_x402_services or inspect_x402_offer for this service.
  3. 03
    Quote, test-buy, then run the governed paid fetch through AXON.

Send this

Prompt for your agent

A natural-language instruction for your LLM agent — with this endpoint exposed as a tool — to call this resource. Not sent to the endpoint; the endpoint consumes the JSON body below.

Pasting this prompt into a raw ChatGPT or unconfigured agent will notexecute the paid endpoint flow. Run it through an agent with the AXON runtime / MCP tools exposed (see “Use with AXON” above) so the 402 challenge, quote, and governed fetch are handled for you.

Take this CSV of sales data, remove duplicates, standardize the date format to ISO 8601, and calculate monthly totals.

Endpoint request body

The JSON payload your agent sends to the endpoint.

application/json
{
  "data": [
    [
      "2024-01-15",
      "Product A",
      "100"
    ],
    [
      "2024-01-20",
      "Product A",
      "100"
    ],
    [
      "2024/02/01",
      "Product B",
      "250"
    ]
  ],
  "instruction": "Remove duplicate rows, standardize dates to YYYY-MM-DD, group by month and product"
}

Advanced HTTP details

For integrators who need the raw protocol surface. Most agents should use AXON above instead of calling these directly.

curl fallback

curl https://gg402.vercel.app/conversational_etl \
  -H "Content-Type: application/json" \
  -H "X-PAYMENT: [signed_payment_envelope]" \
  -d '{"data":[["2024-01-15","Product A","100"],["2024-01-20","Product A","100"],["2024/02/01","Product B","250"]],"instruction":"Remove duplicate rows, standardize dates to YYYY-MM-DD, group by month and product"}'

Payment & settlement details

Raw on-chain settlement parameters. AXON above handles these automatically through quote / test-buy / governed fetch.

baseexact
$0.010
per call
Pay-to address0x9257cd24721e3c06e9f7655b77c283bcd9652132
T/O: 60s asset 0x8335…2913

Price & network

Cheapest call$0.010
Networks
base

Trust & risk

Trust tier Indexed external
Risk flagsNo risks flagged
View JSON bundle

Indexed from facilitator discovery data

Last enriched: