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Get a Document

GET 

/api/v8/partner/documents/:document_id

Veryfi's Get a Document endpoint allows you to retrieve a single Document by ID. Veryfi responds with a Document object and its extracted fields in JSON format, allowing developers to understand the contents of the originally processed document in detail.

Request

Path Parameters

    document_id int64required

    The unique identifier of the document.

Query Parameters

    bounding_boxes boolean

    A field used to determine whether or not to return bounding_box and bounding_region for extracted fields in the Document response.

    confidence_details boolean

    A field used to determine whether or not to return the score and ocr_score fields in the Document response.

    detailed boolean

    This field was deprecated on 2023-08-20. Use bounding_boxes and confidence_details.

    return_audit_trail boolean

    A field used to determine whether or not to return verbose logs in the response.

Responses

The processed document response. Fields with an asterisk will be returned. Contact support to enable any additional fields on your account.

Schema
    anyOf
    external_id string

    Possible values: non-empty

    A custom identification value. Use this if you would like to assign your own ID to documents. This parameter is useful when mapping this document to a service or resource outside Veryfi.

    pdf_url uri

    Possible values: non-empty and <= 2083 characters

    A signed URL to access the auto-generated PDF created from the submitted document. This URL expires 15 minutes after the response object is returned and is resigned during every GET request.

    id integerrequired

    The unique number created to identify the document.

    created_date date-time

    The date and time the invoice or receipt was first submitted and processed in ISO 8601 format.

    updated_date date-time

    The date and time when the last update was made to the Document object in ISO 8601 format.

    img_thumbnail_url uri

    Possible values: non-empty and <= 2083 characters

    A signed URL to access the auto-generated thumbnail created for the submitted document. This URL expires 15 minutes after the response object is returned and is resigned during every GET request.

    accounting_entry_type string

    Possible values: [debit, credit]

    Classifies the document as credit or debit for accounting purposes.

    custom_fields object

    A user-defined dictionary that contains all the custom fields generated by applying specific rules and regular expressions to the extracted data.

    duplicate_of integer

    The ID of the first unique Document. This Document has been identified as a duplicate of another Document.

    exch_rate number

    The exchange rate is calculated by dividing the amount of the currency found on the document by your account's default currency. The exchange rate will be 1 if the document's currency matches your account's default currency or Veryfi cannot find a currency on the document.

    img_blur booleandeprecated

    The value indicating whether or not the image taken with the Lens SDK is blurry. Please use meta.pages.is_blurry instead

    img_file_name string

    Possible values: non-empty

    The filename and extension for the document submitted to Veryfi for processing. This is the filename and extension for the document hosted on Veryfi.

    img_url uri

    Possible values: non-empty and <= 2083 characters

    A signed URL to the original submitted image or the PDF generated from multiple images. The URL expires 15 minutes after the Document Response is returned and is re-assigned on every GET request.

    is_approved boolean

    A user-defined flag that can be assigned to the Document object. This parameter is helpful in expense management use cases.

    is_blurry boolean[]deprecated

    Deprecated. Please use meta.pages.is_blurry instead

    is_document boolean

    The value indicating whether or not the image submitted for processing is a receipt, invoice, or another supported document type.

    is_duplicate boolean

    The value indicating whether or not this Document has been identified as a duplicate of another Document on your account.

    line_items object[]

    A list of the products or services purchased or ordered on the submitted document.

  • Array [
  • id integerrequired

    The unique number created to identify the Line Item object.

    order integerrequired

    The value indicating the position of where the line item appears on the document.

    tags string[]

    Possible values: non-empty

    A user-defined list of identifiers that help to categorize or flag particular types of line items.

    text stringrequired

    Possible values: non-empty and <= 1000 characters

    The complete text returned for the line item, including prices, dates, etc.

    type stringrequired

    Possible values: [room, tax, parking, service, fee, delivery, product, food, alcohol, tobacco, transportation, fuel, refund, discount, payment, giftcard, donation, toll, lottery]

    The classification of the product. The line type predicted by Veryfi, e.g. food.

    product_info object

    Line item extra product info

    anyOf
    expanded_description stringrequired

    Possible values: non-empty

    brand stringrequired

    Possible values: non-empty

    category string[]required

    Possible values: non-empty

    date date

    The date found on the document and associated with the line item in ISO 8601 format.

    description stringrequired

    Possible values: non-empty and <= 1000 characters

    The product or service's extracted name or description excluding date and price.

    full_description string

    Possible values: non-empty and <= 1000 characters

    The item text including dates, weight, etc.

    normalized_description string

    Possible values: non-empty

    The line item description with expanded words

    discount_price number

    The lower price after discount.

    discount_rate number

    The discount percentage that was applied to the line item.

    discount number

    The amount deducted from the total price for the line item.

    price number

    The unit price for the line item.

    quantity number

    The amount or number of units for the line item. This value is computable.

    reference string

    Possible values: non-empty

    section string

    Possible values: non-empty

    A grouping indicated by formatted text on the receipt or invoice.

    sku string

    Possible values: non-empty

    The Stock Keeping Unit (SKU) is the unique code associated with the product for the line item.

    tax_rate number

    The percent at which the individual or corporation is taxed for the line item.

    tax number

    The amount at which the individual or corporation is taxed for the product on this line item.

    total number

    The total price for this line item. This value is computable.

    subtotal number

    Total charges and credits before tip and tax, if applicable. This value is computable.

    unit_of_measure string

    Possible values: non-empty

    The unit of measurement for this line item.

    category string

    Possible values: non-empty

    The category is taken from the line item with the same SKU and/or description. Otherwise from the root category field.

    country_of_origin string

    Possible values: [FO, SI, KH, AD, AO, CR, HT, EG, MA, AW, PE, PH, ZA, TZ, SK, SD, MV, BN, SY, SB, MX, IO, FK, LB, GD, NI, GS, TN, GQ, MK, MG, NO, PT, SC, SZ, BS, BZ, DK, GI, HU, TK, KE, TD, HK, LY, NG, UG, AQ, UZ, NR, BR, MY, ST, PF, TV, LR, GM, MS, CD, AI, IM, JM, KZ, LK, GY, LA, YT, SL, BB, BT, CM, TF, KY, BG, MZ, FI, NL, IN, NU, PG, LC, BW, CU, PY, ZW, CI, DZ, LU, GU, AG, PL, HR, FR, ZM, VE, BF, AT, NC, MQ, JO, EC, MF, GL, AM, GH, BJ, CX, VA, BI, TG, UM, YE, NF, DM, LV, CO, PM, SJ, GT, MU, DO, ER, GG, GW, KM, GP, MM, TJ, TC, SA, FJ, IE, DJ, KP, PW, SM, TL, SO, LI, PN, FM, HN, AR, BE, HM, AZ, UY, BY, CK, GF, NA, SH, WF, EE, MN, AE, ET, IT, GB, ES, VI, QA, CG, CN, GN, AX, JP, VU, SR, CV, PA, MD, KN, BO, LS, RS, GR, VN, CH, LT, MO, BM, MP, EH, RO, IR, OM, IL, ML, MT, CF, RU, TM, AN, PK, TR, MH, PS, UA, IS, AU, KW, BL, BV, ME, GE, KG, MC, AL, BD, WS, BA, IQ, TH, CL, TO, VG, CY, BH, PR, TW, TT, KI, CC, AF, MW, SG, MR, SV, KR, RW, RE, NZ, DE, JE, VC, GA, NE, CZ, US, CA, NP, AS, ID, SE, SN]

    The country of manufacture, production, design, or brand origin where the product comes from.

    custom_fields object

    A user-defined dictionary that contains all the custom fields generated by applying specific rules and regular expressions to the extracted data.

    product_details object[]

    Product lookup details

  • Array [
  • avg_price numberrequired

    The average price of the product

    brand stringrequired

    Possible values: non-empty

    The brand name of the product

    ean stringrequired

    Possible values: non-empty

    European Article Number (EAN) of the product

    extra_fields objectrequired

    Additional fields for the product details

    property name* any

    Additional fields for the product details

    gtin_14 stringrequired

    Possible values: non-empty

    Global Trade Item Number (GTIN-14) of the product

    match_score numberrequired

    Possible values: <= 1

    The match score of the product

    image stringrequired

    Possible values: non-empty

    The image URL of the product

    image_url stringrequired

    Possible values: non-empty

    Alternative field for the image URL of the product

    product_name stringrequired

    Possible values: non-empty

    The name of the product

    segment stringrequired

    Possible values: non-empty

    The market segment of the product

    veryn stringrequired

    Possible values: non-empty

    The veryn identifier of the product

  • ]
  • end_date date

    A service end date identified for the line item in ISO 8601 format.

    gross_total number

    The line item total before deductions.

    hsn string

    Possible values: non-empty

    The Harmonized System Nomenclature (HSN) found for the line item.

    lot string

    Possible values: non-empty

    The batch or lot number for the line item.

    start_date date

    A service start date identified for the line item in ISO 8601 format.

    tax_code string

    Possible values: non-empty

    The classification of goods and services for tax purposes for the line item.

    manufacturer string

    Possible values: non-empty

    The name of the manufacturer of the product for the line item.

    net_total number

    The line item total after deductions.

    upc string

    Possible values: non-empty

    The Universal Product Code (UPC), European Article Number (EAN), or Global Trade Item Number (GTIN) found for the line item on this document will be placed in this field.

    weight string

    Possible values: non-empty

    The weight of the item for the line item. Usually found on logistic invoices.

  • ]
  • tax_lines object[]

    A detailed breakdown of tax elements usually found in a tax table.

  • Array [
  • order integerrequired

    The arrangement of tax lines in relation to each other.

    name stringrequired

    Possible values: non-empty

    The name of the sales tax type.

    rate numberrequired

    The tax rate (percentage) applied to the base amount. This value is computable.

    total numberrequired

    The total amount of tax charged for this particular tax line item. If the document has multiple taxes on it those taxes will be returned in the list inside the taxes field. Note there are a couple of countries in the world that have 3 decimal places after the dot.

    base numberrequired

    The base amount of the tax applied.

    code string

    Possible values: non-empty

    The tax identification code.

    total_inclusive number

    The base rate + tax amount.

  • ]
  • model string

    Possible values: non-empty

    The data extraction model version number that was used to process the document.

    notes string

    Possible values: non-empty

    A user-defined text field that can be used to add any additional document-level information.

    ocr_text string

    The text returned from converting the document into a machine-readable text format.

    payment_links string[]

    Possible values: non-empty

    Document payments links, included pdf hidden links

    reference_number stringdeprecated

    Possible values: non-empty

    Deprecated. Use id.

    status string

    Possible values: [processed, reviewed, archived]

    The value indicating the document's status.

    tags object[]

    A user-defined list of identifiers that help to categorize or flag particular types of documents. The Document object can have multiple tags. You can create tags by API or in Hub.

  • Array [
  • id integerrequired

    The ID of the tag.

    name stringrequired

    Possible values: non-empty

    The name of the tag.

  • ]
  • total_pages integerdeprecated

    Deprecated. Use meta.total_pages.

    warnings string[]

    Possible values: non-empty

    An array of insights that highlight unusual behavior found on a document.

    meta objectrequired

    An object that describes document-related metadata information such as total pages.

    owner stringrequired

    Possible values: non-empty

    The API username for the account that processed the document.

    total_pages integerrequired

    The total number of pages found in the submitted document.

    processed_pages integerrequired

    The number of processed pages for the document. The default limit is 15 pages per document. Use max_processed_pages on the POST request to update the limit.

    pages object[]required
  • Array [
  • height integerrequired
    width integerrequired
    language object[]required

    Page languages in BCP-47 language tag, starting with the most confident prediction.

  • Array [
  • score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information. Returned with confidence_details: true

    value stringrequired

    Possible values: non-empty

    The extracted value.

  • ]
  • screenshot object
    score number

    Possible values: <= 1

    type stringrequired

    Possible values: [mobile_screenshot, other_screenshot, ai_generated]

    The predicted value of the screenshot type if the document is a screenshot.

    is_blurry object

    The processed page is blurry or not

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information. Returned with confidence_details: true

    value booleanrequired

    The extracted value.

  • ]
  • source_documents object[]required

    An array containing meta info about originally submitted documents

  • Array [
  • size_kb integerrequired
    height integerrequired
    width integerrequired
    exif object

    EXIF data from the source document

    property name* any

    EXIF data from the source document

  • ]
  • fraud object

    An object that contains additional information to help check for fraud. Does not work with the parameter boost_mode set to true.

    attribution string

    Possible values: non-empty

    Attribution of Fraud Detector's decision

    decision string

    Possible values: non-empty

    Fraud Detector's decision

    color string

    Possible values: [green, yellow, red]

    Color from Fraud Detector: green means legitimate, yellow means review needed and red means fraud

    pages object[]

    An array containing fraud info about each extracted page

  • Array [
  • anyOf
    is_lcd object
    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information. Returned with confidence_details: true

    value booleanrequired

    The extracted value.

  • ]
  • images object[]deprecated

    deprecated and will be removed at 2023-11-10. Use meta.fraud.pages instead

  • Array [
  • anyOf
    is_lcd boolean

    The value indicating whether or not the image is a picture of an LCD screen.

    score number

    The value indicating how confident the model is about is_lcd prediction.

  • ]
  • score number

    Possible values: <= 1

    Confidence of Fraud Detector in it's prediction

    version string

    Possible values: non-empty

    The Fraud Detector version. The latest version in action while the document was processed. Different versions may have their own ways of calculating the score and deducing the color string value.

    submissions object

    The amount of submissions from specific device id.

    property name* integer
    fraudulent_pdf object

    Results of the pdf analysis.

    property name* number
    types string[]

    Possible values: [other, handwritten characters, digital tampering, generated document, LCD photo, screenshot, not a document, duplicate, high velocity, fraudulent pdf, critical velocity, similar documents, multiple profiles or devices, fraud history, emulated device, blocked device]

    Default value: ``

    List of attributions which marked the document as fraud

    digital_tampering_fields string[]

    Possible values: Value must match regular expression ^(incoterms|rounding|bill_to_name|vendor_bank_name|card_number|vendor_bank_number|total_in_words|so_number|cashback|vendor_address|bill_to_reg_number|hsn|ship_to_address|balance|summary_total|delivery_note_number|abn_number|ship_to_name|tax_base|vin_number|summary_name|final_balance|start_date|account_number|vendor_bank_swift|time|ship_date|vendor_iban|terms|date|bill_to_phone_number|charge_name|total|vendor_reg_number|guest_count|due_date|phone_number|raw_vendor_name|charge_total|start_time|biller_code|total_weight|tax_name|bill_to_vat_number|license_plate_number|previous_balance|delivery_date|po_number|vendor_account_currency|tracking_number|vendor_account_number|fax_number|order_date|subtotal|invoice_number|total_currency_code|delivery|bill_to_email|document_title|reference|tax_code|tip|end_time|vending_person|end_date|vendor_bank_address|bill_to_address|insurance|vendor_web|vat_number|vendor_logo_name|tax|store_number|discount|vending_person_number|vendor_email|tax_rate|total_quantity|line_items\.\d{1,4}\.(?:mnf|discount_price|description|discount_rate|lot|tax_code|unit_of_measure|start_date|tax_rate|section|end_date|taxes|price|weight|quantity|full_description|coo|date|sku|hsn|tax|upc|discount|subtotal|total)|tax_breakdown\.\d{1,4}\.(?:tax_name|tax_inclusive|tax_base|tax|tax_code|tax_rate)|summary\.\d{1,4}\.(?:summary_name|summary_total)|bank_breakdown\.\d{1,4}\.(?:vendor_bank_address|vendor_bank_number|vendor_bank_swift|vendor_bank_name|vendor_iban|vendor_bank_names|vendor_account_currency|vendor_account_number|vendor_bank_addresses|vendor_bank_numbers))$

    List of fields which were digitally tampered. Does not work with the parameter boost_mode set to true.

    fraud_review object

    An object that contains information about the fraud review.

    decision string

    Possible values: [fraud, not fraud, unknown]

    The review decision for the document

    types string[]

    Possible values: [other, handwritten characters, digital tampering, generated document, LCD photo, screenshot, not a document, duplicate, high velocity, fraudulent pdf]

    Default value: ``

    What kind of fraud type

    warnings object[]

    An array of warnings to help catch errors or fraud on the processed document. This is also related to the integrity checks on a document such as subtotal not matching the sum of line item totals. Does not work with the parameter boost_mode set to true.

  • Array [
  • type stringrequired

    Possible values: [tax_rate_missmatch, item_counts_missmatch, totals_missmatch, line_item_amount_missmatch, line_item_repeats, barcode_decoding_issue, barcode_code_missing_in_ocr, logo_vendor_missmatch, malware]

    Type of the warning, e.g. barcode_code_missing_in_ocr. Type is an enumerated field and comes from a defined number of enumerated values.

    message stringrequired

    Possible values: non-empty

    The detailed message about the warning.

  • ]
  • handwritten_fields string[]

    Possible values: Value must match regular expression ^(incoterms|rounding|bill_to_name|vendor_bank_name|card_number|vendor_bank_number|total_in_words|so_number|cashback|vendor_address|bill_to_reg_number|hsn|ship_to_address|balance|summary_total|delivery_note_number|abn_number|ship_to_name|tax_base|vin_number|summary_name|final_balance|start_date|account_number|vendor_bank_swift|time|ship_date|vendor_iban|terms|date|bill_to_phone_number|charge_name|total|vendor_reg_number|guest_count|due_date|phone_number|raw_vendor_name|charge_total|start_time|biller_code|total_weight|tax_name|bill_to_vat_number|license_plate_number|previous_balance|delivery_date|po_number|vendor_account_currency|tracking_number|vendor_account_number|fax_number|order_date|subtotal|invoice_number|total_currency_code|delivery|bill_to_email|document_title|reference|tax_code|tip|end_time|vending_person|end_date|vendor_bank_address|bill_to_address|insurance|vendor_web|vat_number|vendor_logo_name|tax|store_number|discount|vending_person_number|vendor_email|tax_rate|total_quantity|line_items\.\d{1,4}\.(?:mnf|discount_price|description|discount_rate|lot|tax_code|unit_of_measure|start_date|tax_rate|section|end_date|taxes|price|weight|quantity|full_description|coo|date|sku|hsn|tax|upc|discount|subtotal|total)|tax_breakdown\.\d{1,4}\.(?:tax_name|tax_inclusive|tax_base|tax|tax_code|tax_rate)|summary\.\d{1,4}\.(?:summary_name|summary_total)|bank_breakdown\.\d{1,4}\.(?:vendor_bank_address|vendor_bank_number|vendor_bank_swift|vendor_bank_name|vendor_iban|vendor_bank_names|vendor_account_currency|vendor_account_number|vendor_bank_addresses|vendor_bank_numbers))$

    List of fields which were handwritten. Does not work with the parameter boost_mode set to true.

    device_id string

    Possible values: Value must match regular expression ^[0-9a-fA-F]{8}-[0-9a-fA-F]{4}-[0-9a-fA-F]{4}-[0-9a-fA-F]{4}-[0-9a-fA-F]{12}$

    Fingerprint of the device used to process the document.

    device_user_uuid string

    Possible values: Value must match regular expression ^[0-9a-fA-F]{8}-[0-9a-fA-F]{4}-[0-9a-fA-F]{4}-[0-9a-fA-F]{4}-[0-9a-fA-F]{12}$

    Fingerprint of the user who processed the document on a particular device.

    duplicates object[]

    A list of 10 closest matches

  • Array [
  • id integerrequired
    url urirequired

    Possible values: non-empty and <= 2083 characters

    score numberrequired

    Possible values: <= 1

    How close is the match

  • ]
  • source string

    Possible values: [api.email, api.web, api, lens.bill, lens.invoice, lens.long_receipt, lens.other, lens.receipt, lens.web, lens]

    Default value: api

    The source of the document's submission for processing.

    language object[]required

    Document languages in BCP-47 language tag, starting with the most confident prediction.

  • Array [
  • score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information. Returned with confidence_details: true

    value stringrequired

    Possible values: non-empty

    The extracted value.

  • ]
  • ocr_score numberrequired

    Possible values: <= 1

    The average OCR score of the whole document.

    account_number object

    The unique identifier of the customer assigned by the vendor.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    balance object

    The invoice or bill balance.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    barcodes object[]

    An array of barcodes extracted from the document if found.

  • Array [
  • bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    data string

    Possible values: non-empty

    The machine-readable representation of the barcode found on the document.

    type string

    Possible values: non-empty

    The name of the encoding for the barcode. Supported types include: QR Code, PDF417, EAN, UPC, Code128, Code39, I25

  • ]
  • bill_to object

    An object that describes a person or business that is billed for the amount found on the document.

    name object

    The payer's name found in the billing section of the document.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    address object

    The payer's address found in the billing section of the document.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    vat_number object

    The value-added tax identification number (VAT) for the payer and found on the document. VAT numbers can be found on European invoices. For United States invoices, the Employer Identification Number (EIN) of the payer.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    phone_number object

    The payer's phone number found in the billing section of the document.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    reg_number object

    The payer's registration number found in the billing section of the document.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    email object

    The payer's email address found in the billing section of the document.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    parsed_address object

    An object representing detailed address-related information on the document, such as the city, state, street address, unit number, etc. Filled in the original POST request had the parameter parse_address set to true and the corresponding address is found on the document.

    building string

    Possible values: non-empty

    The building name e.g. 'Project 8' or 'Empire State Building'

    city string

    Possible values: non-empty

    The settlement including cities, towns, villages, hamlets, localities, etc.

    country string

    Possible values: non-empty

    The sovereign nations and their dependent territories, anything with an ISO-3166 code.

    country_alpha_2 string

    Possible values: non-empty

    The detected ISO 3166-1 alpha-2 code for a given country.

    postcode string

    Possible values: non-empty

    The postal code used for mail sorting

    state string

    Possible values: non-empty

    A first-level administrative division. Scotland, Northern Ireland, Wales, and England in the UK are mapped to "state" as well

    street_address string

    Possible values: non-empty

    A sum of house_number road, building, unit.

    house string

    Possible values: non-empty

    The venue name e.g. "Brooklyn Academy of Music", and building names e.g. "Empire State Building".

    house_number string

    Possible values: non-empty

    Usually refers to the external (street-facing) building number. In some countries this may be a compound, hyphenated number, which also includes an apartment number, or a block number (a la Japan).

    road string

    Possible values: non-empty

    Street name(s)

    unit string

    Possible values: non-empty

    An apartment, unit, office, lot, or other secondary unit designator.

    level string

    Possible values: non-empty

    The expressions indicating a floor number e.g. "3rd Floor", "Ground Floor", etc.

    staircase string

    Possible values: non-empty

    Numbered/lettered staircase

    entrance string

    Possible values: non-empty

    Numbered/lettered entrance

    po_box string

    Possible values: non-empty

    The post office box, typically found in non-physical (mail-only) addresses.

    suburb string

    Possible values: non-empty

    An unofficial neighborhood name like "Harlem", "South Bronx", or "Crown Heights".

    city_district string

    Possible values: non-empty

    The boroughs or districts within a city that serve some official purpose e.g. "Brooklyn" or "Hackney" or "Bratislava IV".

    island string

    Possible values: non-empty

    Named islands e.g. "Maui"

    state_district string

    Possible values: non-empty

    Usually a second-level administrative division or county.

    country_region string

    Possible values: non-empty

    Informal subdivision of a country without any political status.

    world_region string

    Possible values: non-empty

    Only used for appending "West Indies" after the country name, a pattern frequently used in the English-speaking Caribbean e.g. "Jamaica, West Indies".

    cashback object

    The amount of cash the customer has withdrawn when making a purchase. Cashback can be found on a receipt but does not appear on invoices.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    category object

    A category predicted from sent categories, user categories or default ones.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    confidence_details booleandeprecated

    Deprecated on 2024-12-27.

    country_code object

    The country code of a document, e.g. where it was issued or where the vendor provides services

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: [FO, SI, KH, AD, AO, CR, HT, EG, MA, AW, PE, PH, ZA, TZ, SK, SD, MV, BN, SY, SB, MX, IO, FK, LB, GD, NI, GS, TN, GQ, MK, MG, NO, PT, SC, SZ, BS, BZ, DK, GI, HU, TK, KE, TD, HK, LY, NG, UG, AQ, UZ, NR, BR, MY, ST, PF, TV, LR, GM, MS, CD, AI, IM, JM, KZ, LK, GY, LA, YT, SL, BB, BT, CM, TF, KY, BG, MZ, FI, NL, IN, NU, PG, LC, BW, CU, PY, ZW, CI, DZ, LU, GU, AG, PL, HR, FR, ZM, VE, BF, AT, NC, MQ, JO, EC, MF, GL, AM, GH, BJ, CX, VA, BI, TG, UM, YE, NF, DM, LV, CO, PM, SJ, GT, MU, DO, ER, GG, GW, KM, GP, MM, TJ, TC, SA, FJ, IE, DJ, KP, PW, SM, TL, SO, LI, PN, FM, HN, AR, BE, HM, AZ, UY, BY, CK, GF, NA, SH, WF, EE, MN, AE, ET, IT, GB, ES, VI, QA, CG, CN, GN, AX, JP, VU, SR, CV, PA, MD, KN, BO, LS, RS, GR, VN, CH, LT, MO, BM, MP, EH, RO, IR, OM, IL, ML, MT, CF, RU, TM, AN, PK, TR, MH, PS, UA, IS, AU, KW, BL, BV, ME, GE, KG, MC, AL, BD, WS, BA, IQ, TH, CL, TO, VG, CY, BH, PR, TW, TT, KI, CC, AF, MW, SG, MR, SV, KR, RW, RE, NZ, DE, JE, VC, GA, NE, CZ, US, CA, NP, AS, ID, SE, SN]

    currency_code object

    The currency code in ISO 4217 format. The exchange_rate field will be enriched if the currency found on the document is different from the account's default currency.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information. Returned with confidence_details: true

    value stringrequired

    Possible values: [GYD, NGN, AZN, GNF, COP, KHR, MKD, MXN, TWD, PLN, PYG, NAD, BHD, GTQ, PKR, UYU, ISK, ARS, SHP, ZWD, GHC, EUR, KYD, MOP, PAB, CZK, BSD, THB, SBD, AWG, IDR, YER, CUP, KPW, EGP, LSL, LKR, SEK, KWD, BAM, USD, BND, BYR, MVR, NIO, BOB, KRW, BRL, LAK, BBD, VND, PEN, HUF, MYR, ALL, DKK, TRL, UZS, MUR, MZN, ZAR, GGP, NPR, PHP, SVC, SYP, TTD, IRR, SZL, JEP, HTG, IQD, BZD, JMD, XCD, AMD, GBP, AUD, ANG, CNY, AED, AFN, SRD, KZT, GIP, TVD, GEL, UAH, FJD, IMP, OMR, CHF, UGX, LTL, BMD, SGD, ILS, HRK, QAR, EEK, CAD, RSD, CLP, LBP, SOS, NOK, BGN, HKD, JPY, KGS, RUB, LRD, INR, MNT, DOP, RON, SCR, SAR, CRC, NZD, BWP, HNL, FKP, LVL, TRY, VEF]

    date object

    The date and time found on the document in ISO 8601 format. This value is computable.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value date-timerequired
    default_category object
    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: [other, Job Supplies, Meals & Entertainment, Travel, Automotive, Office Supplies & Software, Food and Groceries, Gifts & Donations, Transportation, Repairs & Maintenance, Utilities, Advertising & Marketing, Legal & Professional Services, Payroll Expenses, Contractors, Rent & Lease, Insurance, Taxes & Licenses, Bank Charges & Fees, Healthcare, Postage & Delivery, Clothing & Shoes, Household, Interest Paid, Training & Education, Dues and Subscriptions]

    delivery_date object

    The date of an order's delivery in ISO 8601 format. Typically found on invoices.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value date-timerequired
    delivery_note_number object

    The unique identification number found on the delivery note. Delivery notes have a similar format to invoices but usually titled 'Delivery Note'.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    discount object

    The amount deducted from the gross price.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value numberrequired
    document_reference_number object

    The identification number for the document. Commonly used to identify items for a particular customer.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    document_title object

    The title found on the document. The title is usually located at the top of the document. Common examples of document titles include Invoice, Vendor Credit, and Purchase Order.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    document_type object

    A classification of the document, such as invoice, purchase_order, receipt, remittance_advice, or other.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: [other, receipt, invoice, statement, purchase_order, check, w9, packing_slip, contract, w8, remittance_advice]

    due_date object

    The date and time the payment is due for an invoice in ISO 8601 format. This value is computable.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value daterequired
    final_balance number

    The invoice balance. If the invoice is paid, the final balance is 0, but if the invoice is not paid, the value is equal to the total.

    guest_count object

    The number of guests or seats extracted from the document.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    incoterms object

    The incoterms to specify who pays and manages the shipment, insurance, documentation, customs clearance, and other logistics.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    insurance object

    The insurance cost. Typically found on invoices.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value numberrequired
    invoice_number object

    The identification number for the document. Typically found on invoices.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    is_money_in object

    This parameter is used in the Expense Management application. The value is true if the document has a refund or credit note.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value booleanrequired
    is_transaction object

    This flag marks card slips as true.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value booleanrequired
    license_plate_number object

    The vehicle license plate number.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    line_items_with_scores object[]

    A list of the products or services purchased or ordered on the submitted document with confidence details.

  • Array [
  • id integerrequired

    The unique number created to identify the Line Item object.

    order integerrequired

    The value indicating the position of where the line item appears on the document.

    tags string[]

    Possible values: non-empty

    A user-defined list of identifiers that help to categorize or flag particular types of line items.

    text stringrequired

    Possible values: non-empty and <= 1000 characters

    The complete text returned for the line item, including prices, dates, etc.

    type stringrequired

    Possible values: [room, tax, parking, service, fee, delivery, product, food, alcohol, tobacco, transportation, fuel, refund, discount, payment, giftcard, donation, toll, lottery]

    The classification of the product. The line type predicted by Veryfi, e.g. food.

    product_info object

    Line item extra product info

    anyOf
    expanded_description stringrequired

    Possible values: non-empty

    brand stringrequired

    Possible values: non-empty

    category string[]required

    Possible values: non-empty

    date object

    The date found on the document and associated with the line item in ISO 8601 format.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value daterequired
    description object

    The product or service's extracted name or description excluding date and price.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    full_description object

    The item text including dates, weight, etc.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    normalized_description object

    The line item description with expanded words

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    discount_price object

    The lower price after discount.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value numberrequired
    discount_rate object

    The discount percentage that was applied to the line item.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value numberrequired
    discount object

    The amount deducted from the total price for the line item.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value numberrequired
    price object

    The unit price for the line item.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value numberrequired
    quantity object

    The amount or number of units for the line item. This value is computable.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value numberrequired
    reference object

    A reference number for the line item found on the document.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    section object

    A grouping indicated by formatted text on the receipt or invoice.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    sku object

    The Stock Keeping Unit (SKU) is the unique code associated with the product for the line item.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    tax_rate object

    The percent at which the individual or corporation is taxed for the line item.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value numberrequired
    tax object

    The amount at which the individual or corporation is taxed for the product on this line item.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value numberrequired
    total object

    The total price for this line item. This value is computable.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value numberrequired
    subtotal object

    Total charges and credits before tip and tax, if applicable. This value is computable.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value numberrequired
    unit_of_measure object

    The unit of measurement for this line item.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    category object

    The category is taken from the line item with the same SKU and/or description. Otherwise from the root category field.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    country_of_origin object

    The country of manufacture, production, design, or brand origin where the product comes from.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: [FO, SI, KH, AD, AO, CR, HT, EG, MA, AW, PE, PH, ZA, TZ, SK, SD, MV, BN, SY, SB, MX, IO, FK, LB, GD, NI, GS, TN, GQ, MK, MG, NO, PT, SC, SZ, BS, BZ, DK, GI, HU, TK, KE, TD, HK, LY, NG, UG, AQ, UZ, NR, BR, MY, ST, PF, TV, LR, GM, MS, CD, AI, IM, JM, KZ, LK, GY, LA, YT, SL, BB, BT, CM, TF, KY, BG, MZ, FI, NL, IN, NU, PG, LC, BW, CU, PY, ZW, CI, DZ, LU, GU, AG, PL, HR, FR, ZM, VE, BF, AT, NC, MQ, JO, EC, MF, GL, AM, GH, BJ, CX, VA, BI, TG, UM, YE, NF, DM, LV, CO, PM, SJ, GT, MU, DO, ER, GG, GW, KM, GP, MM, TJ, TC, SA, FJ, IE, DJ, KP, PW, SM, TL, SO, LI, PN, FM, HN, AR, BE, HM, AZ, UY, BY, CK, GF, NA, SH, WF, EE, MN, AE, ET, IT, GB, ES, VI, QA, CG, CN, GN, AX, JP, VU, SR, CV, PA, MD, KN, BO, LS, RS, GR, VN, CH, LT, MO, BM, MP, EH, RO, IR, OM, IL, ML, MT, CF, RU, TM, AN, PK, TR, MH, PS, UA, IS, AU, KW, BL, BV, ME, GE, KG, MC, AL, BD, WS, BA, IQ, TH, CL, TO, VG, CY, BH, PR, TW, TT, KI, CC, AF, MW, SG, MR, SV, KR, RW, RE, NZ, DE, JE, VC, GA, NE, CZ, US, CA, NP, AS, ID, SE, SN]

    custom_fields object

    A user-defined dictionary that contains all the custom fields generated by applying specific rules and regular expressions to the extracted data.

    end_date object

    A service end date identified for the line item in ISO 8601 format.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value daterequired
    gross_total object

    The line item total before deductions.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value numberrequired
    hsn object

    The Harmonized System Nomenclature (HSN) found for the line item.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    lot object

    The batch or lot number for the line item.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    start_date object

    A service start date identified for the line item in ISO 8601 format.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value daterequired
    tax_code object

    The classification of goods and services for tax purposes for the line item.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    manufacturer object

    The name of the manufacturer of the product for the line item.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    net_total object

    The line item total after deductions.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value numberrequired
    upc object

    The Universal Product Code (UPC), European Article Number (EAN), or Global Trade Item Number (GTIN) found for the line item on this document will be placed in this field.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    weight object

    The weight of the item for the line item. Usually found on logistic invoices.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

  • ]
  • order_date object

    The date when the goods or services were ordered in ISO 8601 format.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value daterequired
    payment object

    An object that represents detailed information about the payment method related to this document.

    card_number object

    The last found digits of a credit or debit card number found on the document.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    display_name string

    Possible values: non-empty

    The card type plus the last four digits of the card number found on the document.

    terms object

    The terms on when and how to pay found on the document. Typically found on invoices.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    type object

    The payment type found on the document.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information. Returned with confidence_details: true

    value stringrequired

    Possible values: [none, master_card, visa, cash, american_express, interac, other, maestro, bancontact, discover, girocard, paypal, applepay, bancomat, octopus, check, bankaxept, card, waon, mada, jcb, bank-to-bank_transfer_bacs, wechat, alipay, pix, unionpay, rupay, bpay, shopeepay, googlepay, giftcard, paypay]

    previous_balance object

    The previous invoice balance.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value numberrequired
    purchase_order_number object

    The unique identification number assigned to a purchase order document. A purchase order is a document given from a buyer to a seller that details the quantity, prices, and total cost of requested goods and services.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    rounding object

    An extracted 'discount' (rounding) that vendors give to customers so they do not have to pay with small coins. For example, if a customer paid with cash and a vendor did not have a change of 4 cents, they would round the number and return 5 cents.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value numberrequired
    server_name object

    The restaurant's server name.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    service_start_date object

    The date indicating the beginning of a service. The start date could be a flight departure date or hotel arrival date in ISO 8601 format.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value daterequired
    service_end_date object

    The date indicating the end of a service. The end date could be a flight arrival date or hotel departure date in ISO 8601 format.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value daterequired
    ship_date object

    The date when the order was or will be shipped in ISO 8601 format.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value daterequired
    ship_to object

    An object that represents the information about a person or business receiving an order.

    address object

    The delivery address found on the document.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    name object

    The name of the person or business who will receive the delivery and found on the document.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    parsed_address object

    An object representing detailed address-related information on the document, such as the city, state, street address, unit number, etc. Filled in the original POST request had the parameter parse_address set to true and the corresponding address is found on the document.

    building string

    Possible values: non-empty

    The building name e.g. 'Project 8' or 'Empire State Building'

    city string

    Possible values: non-empty

    The settlement including cities, towns, villages, hamlets, localities, etc.

    country string

    Possible values: non-empty

    The sovereign nations and their dependent territories, anything with an ISO-3166 code.

    country_alpha_2 string

    Possible values: non-empty

    The detected ISO 3166-1 alpha-2 code for a given country.

    postcode string

    Possible values: non-empty

    The postal code used for mail sorting

    state string

    Possible values: non-empty

    A first-level administrative division. Scotland, Northern Ireland, Wales, and England in the UK are mapped to "state" as well

    street_address string

    Possible values: non-empty

    A sum of house_number road, building, unit.

    house string

    Possible values: non-empty

    The venue name e.g. "Brooklyn Academy of Music", and building names e.g. "Empire State Building".

    house_number string

    Possible values: non-empty

    Usually refers to the external (street-facing) building number. In some countries this may be a compound, hyphenated number, which also includes an apartment number, or a block number (a la Japan).

    road string

    Possible values: non-empty

    Street name(s)

    unit string

    Possible values: non-empty

    An apartment, unit, office, lot, or other secondary unit designator.

    level string

    Possible values: non-empty

    The expressions indicating a floor number e.g. "3rd Floor", "Ground Floor", etc.

    staircase string

    Possible values: non-empty

    Numbered/lettered staircase

    entrance string

    Possible values: non-empty

    Numbered/lettered entrance

    po_box string

    Possible values: non-empty

    The post office box, typically found in non-physical (mail-only) addresses.

    suburb string

    Possible values: non-empty

    An unofficial neighborhood name like "Harlem", "South Bronx", or "Crown Heights".

    city_district string

    Possible values: non-empty

    The boroughs or districts within a city that serve some official purpose e.g. "Brooklyn" or "Hackney" or "Bratislava IV".

    island string

    Possible values: non-empty

    Named islands e.g. "Maui"

    state_district string

    Possible values: non-empty

    Usually a second-level administrative division or county.

    country_region string

    Possible values: non-empty

    Informal subdivision of a country without any political status.

    world_region string

    Possible values: non-empty

    Only used for appending "West Indies" after the country name, a pattern frequently used in the English-speaking Caribbean e.g. "Jamaica, West Indies".

    shipping object

    The cost of shipping or delivery of a package.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value numberrequired
    store_number object

    The subsidiaries, vendor, corporation, or organization identification number used for unique referencing.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    subtotal object

    Total charges and credits before tip and tax, if applicable. This value is computable.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value numberrequired
    tax object

    The tax amount applied to the purchase(s). This value is computable.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value numberrequired
    tax_lines_with_scores object[]

    A detailed breakdown of tax elements usually found in a tax table.

  • Array [
  • order integerrequired

    The arrangement of tax lines in relation to each other.

    name objectrequired

    The name of the sales tax type.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    rate objectrequired

    The tax rate (percentage) applied to the base amount. This value is computable.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value numberrequired
    total objectrequired

    The total amount of tax charged for this particular tax line item. If the document has multiple taxes on it those taxes will be returned in the list inside the taxes field. Note there are a couple of countries in the world that have 3 decimal places after the dot.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value numberrequired
    base objectrequired

    The base amount of the tax applied.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value numberrequired
    code object

    The tax identification code.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    total_inclusive object

    The base rate + tax amount.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value numberrequired
  • ]
  • tip object

    The amount of money that is given to someone for a service, also called gratuity. Usually present on receipts, not invoices. This value is computable.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value numberrequired
    total object

    The gross amount, including subtotal, tax, fees, etc. This value is computable.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value numberrequired
    total_quantity object

    The total quantity of items found on the document. In most cases, this number equals the sum of line item quantities.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value numberrequired
    total_weight object

    The total weight of all items listed on the document. Typically found on invoices.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    tracking_number object

    The unique identifier assigned to a package for referencing its shipping information.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    tracking_numbers object[]

    An array of unique identification numbers assigned to packages for referencing shipping information.

  • Array [
  • anyOf
    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

  • ]
  • vending_person object

    The person or business who has provided services found on the document. This is the same as server_name.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    vending_person_number object

    Identifier for the person or business who has provided services. Typically 'Cashier Number' on receipts or 'Sales Manager Number' on invoices.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    vendor object

    An object containing a detailed breakdown of vendor elements.

    abn_number object

    An Australian Business Number (ABN) is a unique 11-digit number that identifies a business to the government and community and found on the document.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    account_currency object

    The currency of the vendor bank account if indicated. Provides the ability to support multiple bank accounts for bill pay use cases, e.g., a separate bank account for you to pay in Euros and a separate to pay in US Dollars.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: [GYD, NGN, AZN, GNF, COP, KHR, MKD, MXN, TWD, PLN, PYG, NAD, BHD, GTQ, PKR, UYU, ISK, ARS, SHP, ZWD, GHC, EUR, KYD, MOP, PAB, CZK, BSD, THB, SBD, AWG, IDR, YER, CUP, KPW, EGP, LSL, LKR, SEK, KWD, BAM, USD, BND, BYR, MVR, NIO, BOB, KRW, BRL, LAK, BBD, VND, PEN, HUF, MYR, ALL, DKK, TRL, UZS, MUR, MZN, ZAR, GGP, NPR, PHP, SVC, SYP, TTD, IRR, SZL, JEP, HTG, IQD, BZD, JMD, XCD, AMD, GBP, AUD, ANG, CNY, AED, AFN, SRD, KZT, GIP, TVD, GEL, UAH, FJD, IMP, OMR, CHF, UGX, LTL, BMD, SGD, ILS, HRK, QAR, EEK, CAD, RSD, CLP, LBP, SOS, NOK, BGN, HKD, JPY, KGS, RUB, LRD, INR, MNT, DOP, RON, SCR, SAR, CRC, NZD, BWP, HNL, FKP, LVL, TRY, VEF]

    account_number objectrequired

    The vendor's bank account number.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    address objectrequired

    The address of the vendor. This value is computable.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    biller_code object

    The vendor identification code in a payment system.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    bank_breakdown object[]required

    A detailed list of banking information.

  • Array [
  • vendor_account_currency objectrequired
    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: [GYD, NGN, AZN, GNF, COP, KHR, MKD, MXN, TWD, PLN, PYG, NAD, BHD, GTQ, PKR, UYU, ISK, ARS, SHP, ZWD, GHC, EUR, KYD, MOP, PAB, CZK, BSD, THB, SBD, AWG, IDR, YER, CUP, KPW, EGP, LSL, LKR, SEK, KWD, BAM, USD, BND, BYR, MVR, NIO, BOB, KRW, BRL, LAK, BBD, VND, PEN, HUF, MYR, ALL, DKK, TRL, UZS, MUR, MZN, ZAR, GGP, NPR, PHP, SVC, SYP, TTD, IRR, SZL, JEP, HTG, IQD, BZD, JMD, XCD, AMD, GBP, AUD, ANG, CNY, AED, AFN, SRD, KZT, GIP, TVD, GEL, UAH, FJD, IMP, OMR, CHF, UGX, LTL, BMD, SGD, ILS, HRK, QAR, EEK, CAD, RSD, CLP, LBP, SOS, NOK, BGN, HKD, JPY, KGS, RUB, LRD, INR, MNT, DOP, RON, SCR, SAR, CRC, NZD, BWP, HNL, FKP, LVL, TRY, VEF]

    vendor_account_number objectrequired
    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    vendor_bank_address objectrequired

    The address of the vendor bank.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    parsed_address object

    An object representing detailed address-related information on the document, such as the city, state, street address, unit number, etc. Filled in the original POST request had the parameter parse_address set to true and the corresponding address is found on the document.

    building string

    Possible values: non-empty

    The building name e.g. 'Project 8' or 'Empire State Building'

    city string

    Possible values: non-empty

    The settlement including cities, towns, villages, hamlets, localities, etc.

    country string

    Possible values: non-empty

    The sovereign nations and their dependent territories, anything with an ISO-3166 code.

    country_alpha_2 string

    Possible values: non-empty

    The detected ISO 3166-1 alpha-2 code for a given country.

    postcode string

    Possible values: non-empty

    The postal code used for mail sorting

    state string

    Possible values: non-empty

    A first-level administrative division. Scotland, Northern Ireland, Wales, and England in the UK are mapped to "state" as well

    street_address string

    Possible values: non-empty

    A sum of house_number road, building, unit.

    house string

    Possible values: non-empty

    The venue name e.g. "Brooklyn Academy of Music", and building names e.g. "Empire State Building".

    house_number string

    Possible values: non-empty

    Usually refers to the external (street-facing) building number. In some countries this may be a compound, hyphenated number, which also includes an apartment number, or a block number (a la Japan).

    road string

    Possible values: non-empty

    Street name(s)

    unit string

    Possible values: non-empty

    An apartment, unit, office, lot, or other secondary unit designator.

    level string

    Possible values: non-empty

    The expressions indicating a floor number e.g. "3rd Floor", "Ground Floor", etc.

    staircase string

    Possible values: non-empty

    Numbered/lettered staircase

    entrance string

    Possible values: non-empty

    Numbered/lettered entrance

    po_box string

    Possible values: non-empty

    The post office box, typically found in non-physical (mail-only) addresses.

    suburb string

    Possible values: non-empty

    An unofficial neighborhood name like "Harlem", "South Bronx", or "Crown Heights".

    city_district string

    Possible values: non-empty

    The boroughs or districts within a city that serve some official purpose e.g. "Brooklyn" or "Hackney" or "Bratislava IV".

    island string

    Possible values: non-empty

    Named islands e.g. "Maui"

    state_district string

    Possible values: non-empty

    Usually a second-level administrative division or county.

    country_region string

    Possible values: non-empty

    Informal subdivision of a country without any political status.

    world_region string

    Possible values: non-empty

    Only used for appending "West Indies" after the country name, a pattern frequently used in the English-speaking Caribbean e.g. "Jamaica, West Indies".

    vendor_bank_addresses object[]
  • Array [
  • bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

  • ]
  • vendor_bank_name objectrequired

    The name of the bank. Could be part of invoice remittance information.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    vendor_bank_names object[]
  • Array [
  • bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

  • ]
  • vendor_bank_number objectrequired

    The bank routing number. Could be part of invoice remittance information.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    vendor_bank_numbers object[]required

    An array of bank routing numbers.

  • Array [
  • bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

  • ]
  • vendor_bank_swift objectrequired

    The Society for Worldwide Interbank Financial Telecommunication (SWIFT) code is part of the ISO 9362 standards for sending money internationally.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    vendor_iban objectrequired

    The International Bank Account Number (IBAN) is a standard international numbering system developed to identify an overseas bank account.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

  • ]
  • bank_name object

    The name of the bank. Could be part of invoice remittance information.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    bank_number object

    The bank routing number. Could be part of invoice remittance information.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    bank_swift object

    The Society for Worldwide Interbank Financial Telecommunication (SWIFT) code is part of the ISO 9362 standards for sending money internationally.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    category stringdeprecated

    Possible values: non-empty

    Similar to vendor.type

    country_code object

    The country code belonging to a vendor

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: [FO, SI, KH, AD, AO, CR, HT, EG, MA, AW, PE, PH, ZA, TZ, SK, SD, MV, BN, SY, SB, MX, IO, FK, LB, GD, NI, GS, TN, GQ, MK, MG, NO, PT, SC, SZ, BS, BZ, DK, GI, HU, TK, KE, TD, HK, LY, NG, UG, AQ, UZ, NR, BR, MY, ST, PF, TV, LR, GM, MS, CD, AI, IM, JM, KZ, LK, GY, LA, YT, SL, BB, BT, CM, TF, KY, BG, MZ, FI, NL, IN, NU, PG, LC, BW, CU, PY, ZW, CI, DZ, LU, GU, AG, PL, HR, FR, ZM, VE, BF, AT, NC, MQ, JO, EC, MF, GL, AM, GH, BJ, CX, VA, BI, TG, UM, YE, NF, DM, LV, CO, PM, SJ, GT, MU, DO, ER, GG, GW, KM, GP, MM, TJ, TC, SA, FJ, IE, DJ, KP, PW, SM, TL, SO, LI, PN, FM, HN, AR, BE, HM, AZ, UY, BY, CK, GF, NA, SH, WF, EE, MN, AE, ET, IT, GB, ES, VI, QA, CG, CN, GN, AX, JP, VU, SR, CV, PA, MD, KN, BO, LS, RS, GR, VN, CH, LT, MO, BM, MP, EH, RO, IR, OM, IL, ML, MT, CF, RU, TM, AN, PK, TR, MH, PS, UA, IS, AU, KW, BL, BV, ME, GE, KG, MC, AL, BD, WS, BA, IQ, TH, CL, TO, VG, CY, BH, PR, TW, TT, KI, CC, AF, MW, SG, MR, SV, KR, RW, RE, NZ, DE, JE, VC, GA, NE, CZ, US, CA, NP, AS, ID, SE, SN]

    email object

    The vendor's email address.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    external_id string

    Possible values: non-empty

    A custom identification field. Set by matching to a client-provided list of vendors.

    fax_number object

    The fax number of the vendor.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    iban object

    The International Bank Account Number (IBAN) is a standard international numbering system developed to identify an overseas bank account.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    lat number

    The latitude coordinates for the location of this vendor. This is an enriched parameter from a third-party resource not found in the document.

    lng number

    The longitude coordinates for the location of this vendor. This is an enriched parameter from a third-party resource not found in the document.

    logo uri

    Possible values: non-empty and <= 2083 characters

    A URL to the vendor's logo. This is an enriched convenience parameter and is not found on the document.

    logo_name object

    A vendor logo found on the document.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    map_url uri

    Possible values: non-empty and <= 2083 characters

    A URL to the vendor's location on Google Maps. This is an enriched convenience parameter and is not found on the document.

    name object

    The normalized name of the vendor.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    parsed_address object

    An object representing detailed address-related information on the document, such as the city, state, street address, unit number, etc. Filled in the original POST request had the parameter parse_address set to true and the corresponding address is found on the document.

    building string

    Possible values: non-empty

    The building name e.g. 'Project 8' or 'Empire State Building'

    city string

    Possible values: non-empty

    The settlement including cities, towns, villages, hamlets, localities, etc.

    country string

    Possible values: non-empty

    The sovereign nations and their dependent territories, anything with an ISO-3166 code.

    country_alpha_2 string

    Possible values: non-empty

    The detected ISO 3166-1 alpha-2 code for a given country.

    postcode string

    Possible values: non-empty

    The postal code used for mail sorting

    state string

    Possible values: non-empty

    A first-level administrative division. Scotland, Northern Ireland, Wales, and England in the UK are mapped to "state" as well

    street_address string

    Possible values: non-empty

    A sum of house_number road, building, unit.

    house string

    Possible values: non-empty

    The venue name e.g. "Brooklyn Academy of Music", and building names e.g. "Empire State Building".

    house_number string

    Possible values: non-empty

    Usually refers to the external (street-facing) building number. In some countries this may be a compound, hyphenated number, which also includes an apartment number, or a block number (a la Japan).

    road string

    Possible values: non-empty

    Street name(s)

    unit string

    Possible values: non-empty

    An apartment, unit, office, lot, or other secondary unit designator.

    level string

    Possible values: non-empty

    The expressions indicating a floor number e.g. "3rd Floor", "Ground Floor", etc.

    staircase string

    Possible values: non-empty

    Numbered/lettered staircase

    entrance string

    Possible values: non-empty

    Numbered/lettered entrance

    po_box string

    Possible values: non-empty

    The post office box, typically found in non-physical (mail-only) addresses.

    suburb string

    Possible values: non-empty

    An unofficial neighborhood name like "Harlem", "South Bronx", or "Crown Heights".

    city_district string

    Possible values: non-empty

    The boroughs or districts within a city that serve some official purpose e.g. "Brooklyn" or "Hackney" or "Bratislava IV".

    island string

    Possible values: non-empty

    Named islands e.g. "Maui"

    state_district string

    Possible values: non-empty

    Usually a second-level administrative division or county.

    country_region string

    Possible values: non-empty

    Informal subdivision of a country without any political status.

    world_region string

    Possible values: non-empty

    Only used for appending "West Indies" after the country name, a pattern frequently used in the English-speaking Caribbean e.g. "Jamaica, West Indies".

    phone_number object

    The phone number of the vendor.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    raw_address object

    The raw vendor address exactly as found on the document.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    raw_name object

    The raw vendor name exactly as found on the document.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    reg_number object

    The vendor registration number. In the U.S., this would be the Employer Identification Number (EIN). Does not include VAT (Europe) or EIN (US), which are recorded as vat_number.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    type object

    A classification of the vendor, such as drugstore or convenience store. The vendor type predicted by Veryfi. Can also be extracted from third party enrichment

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information. Returned with confidence_details: true

    value object

    The extracted value.

    anyOf

    string

    order_number object

    The unique identification number for the order and set by the vendor. Typically found on invoices.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    vat_number object

    The value-added tax identification number (VAT) for this vendor and found on the document. VAT numbers can be found on European invoices. For United States invoices, the Employer Identification Number (EIN) of the vendor.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    web object

    The vendor's website address (URL).

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    vendors object[]

    An array of all found vendors by vendors.raw_name, including those found with vendor.abn_number and found on the document.

  • Array [
  • bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

  • ]
  • vin_number object

    A vehicle identification number (VIN) is a unique code assigned to every motor vehicle when it's manufactured and found on the document.

    bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

    weights object[]

    An array of the weights found on the document.

  • Array [
  • bounding_region number[]

    Possible values: >= 8, <= 8

    An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.

    bounding_box object[]

    Possible values: >= 5, <= 5

    An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.

  • Array [
  • anyOf

    number

  • ]
  • ocr_score number

    Possible values: <= 1

    The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.

    score number

    Possible values: <= 1

    The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.

    rotation integer

    Possible values: [0, 90, 180, 270]

    The angle of rotation of the document in degrees.

    value stringrequired

    Possible values: non-empty

    The extracted value.

  • ]
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