Field extraction
Pull a field set you define out of any block of text. You name the fields; you get typed values with confidence.
POST/v1/extract
The example in the published schema
charged 00 credits
- auth (bearer key)
- per-key throttle
- validate body
- balance precheck
- run the capability
- charge credits ON SUCCESS ONLY
- JSON
The request body/v1/extract
{ "text": "Order 5561 ships Jul 8 to Denver, CO. Total $412.", "fields": [ "order number", "ship date", "destination", "total" ] }
The responsepublished example
// sending the call
// 0 credits charged so farcurl https://api.thecompound.tech/v1/extract \
-H "Authorization: Bearer $COMPOUND_API_KEY" \
-H "Content-Type: application/json" \
-d '{"text":"Order 5561 ships Jul 8 to Denver, CO. Total $412.","fields":["order number","ship date","destination","total"]}'Scored
7 of 7 field checks passed when the eval suite last ran against production, on 2026-07-08. Every endpoint's score
The Extract & structure guide has this endpoint with its example response. The reference has every parameter.
More from Extract & structure
Classification $0.02/callRoute or tag text against your own taxonomy, a label, a confidence, and a one-line rationale.Structure to your schema $0.06/callAny messy input, text, HTML, an email, plus YOUR JSON schema → output shaped to it, validated against your required fields and property types, with an automatic corrective retry and a `valid` flag.Record normalization $0.05/batchA batch of messy records → clean canonical rows, with a change log of every fix (casing, formats, dedup-ready values).Entity matching $0.08/runTwo record sets → which rows are the same real-world thing, with confidence and reasoning. Fuzzy names, typos, aliases handled.Batch categorization $0.03/batchUp to a hundred items against your taxonomy in one call, products, transactions, tickets, each with a confidence.