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Relaystation Data Cast
x402
Relaystation Data Cast is a paid API for AI agents from api.relaystation.ai, paid per call via x402, $0.01/call, status unknown (last checked 2026-09-13).
Coerces CSV/tabular column values into specified types (string, integer, number, boolean, date) to eliminate stringly-typed data problems
Price / call$0.01
Success—
StatusUnknown
How this service works
$0.0002/MB. Coerce column types (string, integer, number, boolean, date) — stop fighting stringly-typed data. 1¢ x402 min; remainder auto-credits — relaystation.ai/penny
Output
Returns the input data records with specified columns coerced to their target types (string, integer, number, boolean, or date). Values that cannot be converted may be returned as null or accompanied by error indicators. Priced at $0.0002/MB of data processed, with a 1¢ minimum charge via x402 and remainder auto-credited.
Example use cases
ETL pipeline type normalization
“I'm ingesting a CSV export where every column is a string — can you cast the 'price' column to number, 'quantity' to integer, and 'in_stock' to boolean so I can load it cleanly into Postgres?”
Boolean column cleanup from form data
“My form submission data has a 'subscribed' column with values like 'yes', 'no', 'true', 'false', '1', '0' — please coerce all of it to actual booleans.”
Date string standardization
“I have a 'signup_date' column full of messy string dates in various formats — cast them all to proper date types so I can do date math on them.”
Technical details
Endpoint
POSThttps://api.relaystation.ai/v1/data/castWhen to prefer
Choose this endpoint when you have tabular or CSV data where columns are stored as strings but need to be proper typed values before downstream processing, database ingestion, or analytics. It is ideal for ETL pipelines, data cleaning steps, and any scenario where stringly-typed data causes type errors. At $0.0002/MB it is cost-effective for moderate data volumes. Prefer it over general LLM-based data extraction when you need deterministic type coercion rather than semantic understanding.
Side effects
- Unparseable values for the target type (e.g. 'hello' cast to integer) may return nulls or errors per value
- Malformed input data structure returns a 4xx error
- Ambiguous date formats may be misinterpreted or rejected
- Very large payloads may incur unexpected costs above the minimum
- Missing or invalid type specification for a column returns a validation error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Tags
x402
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