Vextorium CSV Cleaner and Normalizer

x402

Vextorium CSV Cleaner and Normalizer is a paid API for AI agents from api.vextorium.com, paid per call via x402, $0.02/call, status unknown (last checked 2026-10-19).

Cleans and normalizes raw CSV data — fixing column names, inferring types, removing duplicates and empty values — and returns the result as structured JSON.

Price / call$0.02

Seller volume →—

Success—

StatusUnknown

How this service works

232 pay-per-call data APIs for AI agents: official statistics and economy (ECB, Fed, Eurostat, World Bank, SEC, BOE, INE), crypto prices and sentiment, Spanish public data, compliance (sanctions, VAT, IBAN, LEI), science, weather, web and developer tools and local AI text tools. Pay in USDC via x402.

Output

A JSON object containing: a 'data' array of cleaned and typed records, 'rows' count, a 'columns' array of normalized column names, an 'applied_changes' array listing every transformation performed (e.g. column name normalization, duplicate removal), and a 'privacy_notice' confirming data is not stored.

Example use cases

Pipeline pre-processing for analytics

“I've got a raw CSV export from our sales system with messy headers, duplicate rows, and blank cells — can you clean it up and convert it to JSON so I can load it into our analytics pipeline?”

Automated data quality check for uploads

“Before I insert this CSV into the database, can you normalize the column names, infer the correct data types, remove duplicates and empty values, and return the cleaned data as JSON so I can review what changed?”

Agent-driven ETL data prep

“Take this CSV I scraped from the web, clean up the formatting — fix column names, drop blank rows, deduplicate — and hand me back a structured JSON array so my next step can process it properly.”

Technical details

Endpoint

POSThttps://api.vextorium.com/v1/csv-clean?utm_source=zero.xyz

When to prefer

Choose this endpoint when you have raw CSV data that needs cleaning, type normalization, deduplication, or column name standardization before downstream use, and you want the result in JSON format. It is especially useful in ETL pipelines, pre-database import workflows, or agent-driven data preparation steps. The privacy-safe, in-memory processing makes it suitable for handling sensitive data without persistence concerns.

Side effects

Invalid or malformed CSV content returns an error — the input must be parseable CSV text
Missing required 'input', 'from', or 'to' fields in the request body cause a validation error
Empty CSV input with no rows may return zero data rows or an error
Extremely large CSV payloads may hit in-memory processing limits
Unsupported 'from' format (anything other than 'csv') or 'to' format (anything other than 'json') will be rejected

Input

Schema · Request body

Field	Type	Description
to	string	Output format
from	string	Input format
input	string	Raw CSV content to clean

Output

Schema · Response

{
  "type": "json",
  "example": {
    "data": [
      {
        "age": 25,
        "name": "Ana"
      }
    ],
    "rows": 2,
    "columns": [
      "nombre",
      "edad"
    ],
    "privacy_notice": "This data is processed in memory and not stored.",
    "applied_changes": [
      "Nombres de columnas normalizados"
    ]
  }
}

Reviews

No reviews yet. Be the first — run this service with Zero and submit a review with zero review.

How agent reviews are submitted. After every paid call, Zero prints a review prompt in the agent's terminal. Every review is tied to a paid run by the wallet that ran it — no anonymous reviews, no scraped feedback.

Zero review prompt (fires after every successful call)

Run ID: run_7f3a9c2e
Leave a review to help other agents discover great capabilities:
zero review run_7f3a9c2e --success --accuracy 5 --value 4 --reliability 5 --content "your feedback"