{"uid":"cap_Zm8KMn-3Ae8VnIkbN5Zi8","slug":"aayat-ai-json-extraction-79aa38c5","name":"Aayat AI JSON Extraction","description":"AI structured extraction: give a URL (web page, PDF, Word, Excel...) or text plus your own JSON Schema, get back JSON that fits it. POST {\"url\": \"...\", \"schema\": {\"type\": \"object\", \"properties\": {...}}, \"instructions\": \"optional\"}. Great for prices, contacts, specs, events, invoices and tables. Uses Llama 3.3 70B in JSON mode. Up to 40,000 characters of source; failures are not charged.","url":"https://aayatai.com/extract-json?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"url":{"type":"string","format":"uri","maxLength":2048,"description":"Page or document to read (use this or text)."},"text":{"type":"string","maxLength":40000,"description":"Text to read (use this or url)."},"schema":{"type":"object","description":"JSON Schema describing the JSON you want back."},"instructions":{"type":"string","maxLength":800,"description":"Extra guidance, e.g. 'prices in GBP, ignore ads'."}}},"responseSchema":null,"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.03","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":"$0.03/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.03","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.03","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_rLgyHPbGbMDSbEYyPWWov","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.03","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Extracts structured JSON from any web page, PDF, Word, Excel, or raw text using a caller-supplied JSON Schema and Llama 3.3 70B","exampleAgentPrompt":"Pull the product name, price, and availability from https://example.com/product/123 and return it as JSON with fields: name (string), price (number), currency (string), and in_stock (boolean).","exampleUseCases":[{"title":"Invoice data extraction from PDF","prompt":"Extract the vendor name, invoice number, line items with quantities and unit prices, and total amount due from this invoice PDF: https://mybusiness.com/invoices/inv-2024-0042.pdf — return it as structured JSON."},{"title":"Competitor price monitoring","prompt":"Scrape the current prices and product names from https://competitor.com/pricing and give me back a JSON array where each item has a plan_name and monthly_price field — ignore any annual pricing rows."},{"title":"Event details from event page","prompt":"Grab the event name, date, location, ticket price, and organizer contact email from https://eventsite.com/events/summer-conf-2025 and return them as a JSON object with those exact fields."}],"resultDescription":"A JSON object conforming to the caller-supplied JSON Schema, populated with values extracted from the source URL or text. Fields not found in the source are typically null or omitted. Failures (e.g. unreachable URL, content too long) are not charged.","failureModes":["URL unreachable or returns non-200 — extraction fails, not charged","Document exceeds 40,000 character limit — truncated or rejected","Schema is too complex or ambiguous — LLM may hallucinate or omit fields","Source page requires JavaScript rendering — static content only","PDF/Word parsing may fail for scanned or image-based documents","Instructions conflict with schema — unpredictable field population"],"whenToPreferThis":"Choose this endpoint when you need to turn arbitrary web pages, PDFs, Word docs, Excel files, or raw text into a specific JSON structure you define. It is especially well-suited for ad-hoc extraction tasks where the schema varies per use case, such as scraping prices, parsing invoices, extracting contacts, or pulling event details. Prefer it over general-purpose LLMs when you need guaranteed JSON-mode output conforming to your schema and want per-call pay-as-you-go pricing with no charge on failures.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-02T18:43:22.733Z","isFirstParty":false,"canonicalSlug":"aayat-ai-json-extraction-79aa38c5"}