{"uid":"cap_MBCPFCSAOGwxG4syf8lS-","slug":"orbonomy-llm-field-extractor-bfd8484b","name":"Orbonomy LLM Field Extractor","description":"50+ pay-per-call API endpoints across accommodation, AI, content, fact-checking, and data services. Powered by x402 protocol.","url":"https://backup-v2api.orbonomy.xyz/api/llm/extract","method":"POST","headers":{},"bodySchema":{"type":"object","required":["text","fields","format"],"properties":{"text":{"type":"string"},"fields":{"type":"array"},"format":{"type":"string"}}},"responseSchema":{"type":"object","properties":{"success":{"type":"boolean"}}},"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.1","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"probe","requiresHandshake":false,"reviewCount":0,"rating":{"score":"0.00","successRate":"0.00","reviews":0,"stars":null,"state":"unrated"},"availabilityStatus":"unknown","priceObserved":null,"sessionDeposit":null,"pricing":{"kind":"static","summary":"$0.1/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.1","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.1","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_JjxFJKa3zKyYOT2nP9w9D","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.1","costPer":"request","priority":0,"asset":null,"unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Extracts specified structured fields from free-form text using LLM processing, returning results in a requested format","exampleAgentPrompt":"Extract the fields 'company_name', 'founding_year', and 'headquarters_city' from this text in JSON format: 'Acme Corp was founded in 1998 and is headquartered in Austin, Texas. They specialize in manufacturing industrial widgets.'","exampleUseCases":[{"title":"Customer feedback analysis for support teams","prompt":"Go through these customer reviews and pull out the main complaint, sentiment, and product mentioned for each one. Give me back a CSV with those three columns so I can sort by sentiment."},{"title":"Resume parsing for recruiter workflows","prompt":"I have a batch of resumes in plain text. Extract the candidate's name, email, phone number, most recent job title, and years of experience from each one. Return it as JSON so I can load it into our ATS."},{"title":"Invoice data extraction from email bodies","prompt":"Parse these forwarded invoice emails and grab the vendor name, invoice number, total amount, and due date from each message. Format it as CSV so I can reconcile it against our accounting records."}],"resultDescription":"A JSON object with a 'success' boolean and the extracted field values mapped to the requested field names in the specified output format (e.g. JSON or CSV).","failureModes":["Missing required fields (text, fields array, or format) returns a 400 error","Ambiguous or unrecognizable field names may result in empty or null values","Very long text inputs may time out or be truncated","Invalid format specifier may cause parsing errors","LLM hallucination may result in incorrect extractions for fields not clearly present in the text","Payment failure via x402 protocol returns 402 Payment Required"],"whenToPreferThis":"Use this endpoint when you need to extract specific named fields from unstructured or semi-structured text using LLM intelligence, especially when the fields are not reliably parseable by regex or rules. Prefer this over general NLP pipelines when you need flexible field specification at call time and pay-per-use pricing.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-09-14T00:51:32.639Z","isFirstParty":false}