{"uid":"cap_-gmiVBTP1-Ohqc8LRj0TN","slug":"vextorium-text-extract-numbers-8cd0d367","name":"Vextorium Text Extract Numbers","description":"Extract and normalize every number in a text: amounts with currency (€, $, USDC, BTC...), percentages, multipliers (k, million, bn) and plain figures, understanding both 1.234,56 and 1,234.56, with totals per currency.","url":"https://api.vextorium.com/v1/text-extract-numbers?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"text":{"type":"string"},"decimal":{"enum":["auto",",","."],"type":"string"}}},"responseSchema":{"type":"json","example":{"amounts":[{"text":"$1,234.56 million","value":1234560000,"currency":"USD"},{"text":"250 USDC","value":250,"currency":"USDC"}],"numbers":[],"percentages":[{"text":"15%","value":15}],"sum_per_currency":{"BTC":0.05,"USD":1234560000,"USDC":250},"decimal_separator":"."}},"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.003","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":"$0.003/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.003","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.003","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_DweF-f9xLRi8uqwjlCule","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.003","costPer":"request","priority":0,"asset":"EPjFWdd5AufqSSqeM2qN1xzybapC8G4wEGGkZwyTDt1v","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Extracts all numbers, monetary amounts, and percentages from a text string, parsing and normalizing them into structured values with currency detection and per-currency sums.","exampleAgentPrompt":"Extract all the numbers, monetary amounts, and percentages from this text and group the totals by currency: 'The fund raised $1,234.56 million, received 250 USDC, and returned 15% to investors.'","exampleUseCases":[{"title":"Parse invoice totals from email","prompt":"Pull out all the dollar amounts and percentages from this invoice email text and give me the total USD: 'Invoice #1042: subtotal $4,500.00, tax $337.50 (7.5%), shipping $25.00, total $4,862.50.'"},{"title":"Extract crypto amounts from trade summary","prompt":"Find every number, amount, and currency mentioned in this trading summary and sum them up by currency: 'Bought 0.05 BTC at $62,000, sold 500 USDC, fee was 0.1%.'"},{"title":"Analyze financial figures in news article","prompt":"Extract all the monetary figures and percentages from this paragraph using dot as decimal separator: 'Revenue grew 12.5% to $3.2 billion, while operating costs fell by $450 million.'"}],"resultDescription":"A JSON object containing: an 'amounts' array (each with the original text, parsed numeric value, and currency code), a 'numbers' array of plain numeric values, a 'percentages' array (each with original text and value), a 'sum_per_currency' object aggregating totals by currency code, and the detected 'decimal_separator'.","failureModes":["Missing required 'text' field in body returns a validation error","Ambiguous decimal separators (when 'auto' cannot determine format) may produce incorrect parsed values","Text with no recognizable numbers returns empty arrays and null sums","Very long text inputs may time out or hit size limits","Non-standard currency symbols may not be recognized and could be omitted from sum_per_currency"],"whenToPreferThis":"Use this endpoint when you need to extract and normalize all numeric data (amounts, percentages, plain numbers) from unstructured text in one call, especially when the text contains multiple currencies or mixed decimal formats. It is the right choice over regex-based solutions when you need currency detection, automatic decimal separator inference, and per-currency aggregation simultaneously. Prefer it over general NLP APIs when you specifically need structured numeric extraction with financial awareness.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T12:37:46.771Z","isFirstParty":false,"canonicalSlug":"vextorium-text-extract-numbers-8cd0d367"}