Update a W-2

PUT 
/api/v8/partner/w2s/:document_id

Veryfi's Update a Document by ID endpoint allows you to change a Document that Veryfi's Machine Learning models have already processed. This feature will enable users to update Documents previously processed by Veryfi to ensure data extraction accuracy. Updating a Document is especially useful for correcting mistakes and updating information over time. By changing a processed Document, Veryfi's Machine Learning models can re-learn the updated information, allowing them to stay accurate and up-to-date.

Request

Path Parameters

document_id int64required

The unique identifier of the document.

application/json

Body

external_id stringdeprecated

Possible values: non-empty

Deprecated 2025-01-09, use meta.external_id instead.

meta object

external_id stringrequired

Possible values: non-empty

Responses

200

A processed W-2 response.

application/json

Schema

Schema

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.

meta object

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-timerequired
updated_date date-timerequired
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.

advance_eic_payment objectrequired
The total amount of any Earned Income Credit (EIC) payment found in Box 9 of the W-2.
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
MOD1
number
MOD2
integer
]
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
employee_ssn objectrequired

The Social Security Number (SSN) found in Box A of the W-2.

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

MOD1

number

MOD2

integer

]

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.

ein objectrequired

The Employer Identification Number (EIN) found in Box B of the W-2.

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

MOD1

number

MOD2

integer

]

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.

employer_name objectrequired

The employer name found in Box C of the W-2.

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

MOD1

number

MOD2

integer

]

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.

employer_address objectrequired

The employer address found in Box C of the W-2.

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

MOD1

number

MOD2

integer

]

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.

control_number objectrequired

The control number found in Box D of the W-2.

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

MOD1

number

MOD2

integer

]

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.

employee_name objectrequired

The full name of the employee found in Box E of the W-2.

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

MOD1

number

MOD2

integer

]

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.

employee_address objectrequired

The address of the employee found in Box F of the W-2.

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

MOD1

number

MOD2

integer

]

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.

wages_other_comps objectrequired
The total taxable income paid found in Box 1 of the W-2.
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
MOD1
number
MOD2
integer
]
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
federal_income_tax objectrequired
The total amount of federal income tax withheld found in Box of the W-2.
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
MOD1
number
MOD2
integer
]
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
ss_wages objectrequired
The total wages subject to social security tax found in Box 3 of the W-2.
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
MOD1
number
MOD2
integer
]
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
ss_tax objectrequired
The amount of social security tax withheld found in Box 4 of the W-2.
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
MOD1
number
MOD2
integer
]
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
medicare_wages objectrequired
The total wages, tips and other compensation that are subject to Medicare taxes found in Box 5 of the W-2.
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
MOD1
number
MOD2
integer
]
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
medicare_tax objectrequired
The amount of Medicare tax withheld from your Medicare taxable wages, tips and other compensation found in Box 6 of the W-2.
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
MOD1
number
MOD2
integer
]
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
ss_tips objectrequired
The amount of earned money through tips found in Box 7 of the W-2.
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
MOD1
number
MOD2
integer
]
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
allocated_tips objectrequired
The amount the employer allocated to tips found in Box 8 of the W-2.
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
MOD1
number
MOD2
integer
]
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
dependent_care_benefits objectrequired
The amount the employer provided or paid for dependent care benefits found in Box 10 of the W-2.
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
MOD1
number
MOD2
integer
]
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
non_qualified_plans objectrequired
The amount of retirement savings the employer sponsored and is tax deferred found in Box 11 of the W-2.
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
MOD1
number
MOD2
integer
]
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
state objectrequired

The two-letter code representing the state found in Box 15 of the W-2. For example, California would be CA.

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

MOD1

number

MOD2

integer

]

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.

employer_state_id objectrequired

The employer identification number found in Box 15 of the W-2.

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

MOD1

number

MOD2

integer

]

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.

state_wages_tips objectrequired
The employer identification number found in Box 15 of the W-2.
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
MOD1
number
MOD2
integer
]
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
state_income_tax objectrequired
The total state income taxes that were withheld found in Box 17 of the W-2.
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
MOD1
number
MOD2
integer
]
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
local_wages_tips objectrequired
The total local taxable gross pay found in Box 18 of the W-2.
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
MOD1
number
MOD2
integer
]
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
local_income_tax objectrequired
The total local income tax withheld found in Box 19 of the W-2.
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
MOD1
number
MOD2
integer
]
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
locality_name objectrequired

The locality name found in Box 20 of the W-2.

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

MOD1

number

MOD2

integer

]

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.

field_12a_col1 objectrequired

The name of another type of compensation or reduction to taxable income found in Box 12 of the W-2. For example, health savings account contributions, group life insurance, 403(b) contributions, and more.

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

MOD1

number

MOD2

integer

]

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.

field_12a_col2 objectrequired
The amount for other types of compensations or reduction to taxable income found in Box 12 of the W-2.
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
MOD1
number
MOD2
integer
]
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
field_12b_col1 objectrequired

The name of another type of compensation or reduction to taxable income found in Box 12 of the W-2. For example, health savings account contributions, group life insurance, 403(b) contributions, and more.

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

MOD1

number

MOD2

integer

]

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.

field_12b_col2 objectrequired
The amount for other types of compensations or reduction to taxable income found in Box 12 of the W-2.
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
MOD1
number
MOD2
integer
]
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
field_12c_col1 objectrequired

The name of another type of compensation or reduction to taxable income found in Box 12 of the W-2. For example, health savings account contributions, group life insurance, 403(b) contributions, and more.

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

MOD1

number

MOD2

integer

]

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.

field_12c_col2 objectrequired
The amount for other types of compensations or reduction to taxable income found in Box 12 of the W-2.
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
MOD1
number
MOD2
integer
]
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
field_12d_col1 objectrequired

The name of another type of compensation or reduction to taxable income found in Box 12 of the W-2. For example, health savings account contributions, group life insurance, 403(b) contributions, and more.

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

MOD1

number

MOD2

integer

]

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.

field_12d_col2 objectrequired
The amount for other types of compensations or reduction to taxable income found in Box 12 of the W-2.
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
MOD1
number
MOD2
integer
]
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
is_13a objectrequired
A checkbox field representing if the individual worked as a statutory employee found in Box 13 of the W-2.
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
MOD1
number
MOD2
integer
]
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_13b objectrequired
A checkbox field representing if the individual participated in an employer sponsored retirement plan found in Box 13 of the W-2.
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
MOD1
number
MOD2
integer
]
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_13c objectrequired
A checkbox field representing if the individual received sick pay through a third party source found in Box 13 of the W-2.
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
MOD1
number
MOD2
integer
]
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
states object[]required
A collection of objects that represent state employer id, wages, tips, and more found in Box 15 - 20 of the W-2.
Array [
state objectrequired
The two-letter code representing the state found in Box 15 of the W-2. For example, California would be CA.
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
MOD1
number
MOD2
integer
]
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.
employer_state_id objectrequired
The employer identification number found in Box 15 of the W-2.
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
MOD1
number
MOD2
integer
]
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.
state_wages_tips objectrequired
The total state taxable gross pay found in Box 16 of the W-2.
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
MOD1
number
MOD2
integer
]
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
state_income_tax objectrequired
The total state income taxes that were withheld found in Box 17 of the W-2.
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
MOD1
number
MOD2
integer
]
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
local_wages_tips objectrequired
The total state taxable gross pay found in Box 16 of the W-2.
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
MOD1
number
MOD2
integer
]
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
local_income_tax object
The total local income tax withheld found in Box 19 of the W-2.
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
MOD1
number
MOD2
integer
]
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
locality_name objectrequired
The locality name found in Box 20 of the W-2.
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
MOD1
number
MOD2
integer
]
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.
]
field_14_other object[]required
An object representing any other tax information that doesn't fit into other W-2 Boxes. For example, this field can be auto allowance, social club membership, travel reimbursement, and more.
Array [
column_1 objectrequired
This field is used for any other tax information that doesn't fit into other W-2 Boxes. For example, this field can be auto allowance, social club membership, travel reimbursement, and more.
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
MOD1
number
MOD2
integer
]
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.
column_2 object
The value for the additional tax 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
MOD1
number
MOD2
integer
]
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
]

Example (from schema)

{
  "external_id": "string",
  "meta": {
    "external_id": "string"
  },
  "pdf_url": "string",
  "id": 0,
  "created_date": "2025-01-25T20:06:08.188Z",
  "updated_date": "2025-01-25T20:06:08.188Z",
  "img_thumbnail_url": "string",
  "advance_eic_payment": {
    "bounding_region": [
      0
    ],
    "bounding_box": [
      0,
      0
    ],
    "ocr_score": 0,
    "score": 0,
    "rotation": 0,
    "value": 0
  },
  "employee_ssn": {
    "bounding_region": [
      0
    ],
    "bounding_box": [
      0,
      0
    ],
    "ocr_score": 0,
    "score": 0,
    "rotation": 0,
    "value": "string"
  },
  "ein": {
    "bounding_region": [
      0
    ],
    "bounding_box": [
      0,
      0
    ],
    "ocr_score": 0,
    "score": 0,
    "rotation": 0,
    "value": "string"
  },
  "employer_name": {
    "bounding_region": [
      0
    ],
    "bounding_box": [
      0,
      0
    ],
    "ocr_score": 0,
    "score": 0,
    "rotation": 0,
    "value": "string"
  },
  "employer_address": {
    "bounding_region": [
      0
    ],
    "bounding_box": [
      0,
      0
    ],
    "ocr_score": 0,
    "score": 0,
    "rotation": 0,
    "value": "string"
  },
  "control_number": {
    "bounding_region": [
      0
    ],
    "bounding_box": [
      0,
      0
    ],
    "ocr_score": 0,
    "score": 0,
    "rotation": 0,
    "value": "string"
  },
  "employee_name": {
    "bounding_region": [
      0
    ],
    "bounding_box": [
      0,
      0
    ],
    "ocr_score": 0,
    "score": 0,
    "rotation": 0,
    "value": "string"
  },
  "employee_address": {
    "bounding_region": [
      0
    ],
    "bounding_box": [
      0,
      0
    ],
    "ocr_score": 0,
    "score": 0,
    "rotation": 0,
    "value": "string"
  },
  "wages_other_comps": {
    "bounding_region": [
      0
    ],
    "bounding_box": [
      0,
      0
    ],
    "ocr_score": 0,
    "score": 0,
    "rotation": 0,
    "value": 0
  },
  "federal_income_tax": {
    "bounding_region": [
      0
    ],
    "bounding_box": [
      0,
      0
    ],
    "ocr_score": 0,
    "score": 0,
    "rotation": 0,
    "value": 0
  },
  "ss_wages": {
    "bounding_region": [
      0
    ],
    "bounding_box": [
      0,
      0
    ],
    "ocr_score": 0,
    "score": 0,
    "rotation": 0,
    "value": 0
  },
  "ss_tax": {
    "bounding_region": [
      0
    ],
    "bounding_box": [
      0,
      0
    ],
    "ocr_score": 0,
    "score": 0,
    "rotation": 0,
    "value": 0
  },
  "medicare_wages": {
    "bounding_region": [
      0
    ],
    "bounding_box": [
      0,
      0
    ],
    "ocr_score": 0,
    "score": 0,
    "rotation": 0,
    "value": 0
  },
  "medicare_tax": {
    "bounding_region": [
      0
    ],
    "bounding_box": [
      0,
      0
    ],
    "ocr_score": 0,
    "score": 0,
    "rotation": 0,
    "value": 0
  },
  "ss_tips": {
    "bounding_region": [
      0
    ],
    "bounding_box": [
      0,
      0
    ],
    "ocr_score": 0,
    "score": 0,
    "rotation": 0,
    "value": 0
  },
  "allocated_tips": {
    "bounding_region": [
      0
    ],
    "bounding_box": [
      0,
      0
    ],
    "ocr_score": 0,
    "score": 0,
    "rotation": 0,
    "value": 0
  },
  "dependent_care_benefits": {
    "bounding_region": [
      0
    ],
    "bounding_box": [
      0,
      0
    ],
    "ocr_score": 0,
    "score": 0,
    "rotation": 0,
    "value": 0
  },
  "non_qualified_plans": {
    "bounding_region": [
      0
    ],
    "bounding_box": [
      0,
      0
    ],
    "ocr_score": 0,
    "score": 0,
    "rotation": 0,
    "value": 0
  },
  "state": {
    "bounding_region": [
      0
    ],
    "bounding_box": [
      0,
      0
    ],
    "ocr_score": 0,
    "score": 0,
    "rotation": 0,
    "value": "string"
  },
  "employer_state_id": {
    "bounding_region": [
      0
    ],
    "bounding_box": [
      0,
      0
    ],
    "ocr_score": 0,
    "score": 0,
    "rotation": 0,
    "value": "string"
  },
  "state_wages_tips": {
    "bounding_region": [
      0
    ],
    "bounding_box": [
      0,
      0
    ],
    "ocr_score": 0,
    "score": 0,
    "rotation": 0,
    "value": 0
  },
  "state_income_tax": {
    "bounding_region": [
      0
    ],
    "bounding_box": [
      0,
      0
    ],
    "ocr_score": 0,
    "score": 0,
    "rotation": 0,
    "value": 0
  },
  "local_wages_tips": {
    "bounding_region": [
      0
    ],
    "bounding_box": [
      0,
      0
    ],
    "ocr_score": 0,
    "score": 0,
    "rotation": 0,
    "value": 0
  },
  "local_income_tax": {
    "bounding_region": [
      0
    ],
    "bounding_box": [
      0,
      0
    ],
    "ocr_score": 0,
    "score": 0,
    "rotation": 0,
    "value": 0
  },
  "locality_name": {
    "bounding_region": [
      0
    ],
    "bounding_box": [
      0,
      0
    ],
    "ocr_score": 0,
    "score": 0,
    "rotation": 0,
    "value": "string"
  },
  "field_12a_col1": {
    "bounding_region": [
      0
    ],
    "bounding_box": [
      0,
      0
    ],
    "ocr_score": 0,
    "score": 0,
    "rotation": 0,
    "value": "string"
  },
  "field_12a_col2": {
    "bounding_region": [
      0
    ],
    "bounding_box": [
      0,
      0
    ],
    "ocr_score": 0,
    "score": 0,
    "rotation": 0,
    "value": 0
  },
  "field_12b_col1": {
    "bounding_region": [
      0
    ],
    "bounding_box": [
      0,
      0
    ],
    "ocr_score": 0,
    "score": 0,
    "rotation": 0,
    "value": "string"
  },
  "field_12b_col2": {
    "bounding_region": [
      0
    ],
    "bounding_box": [
      0,
      0
    ],
    "ocr_score": 0,
    "score": 0,
    "rotation": 0,
    "value": 0
  },
  "field_12c_col1": {
    "bounding_region": [
      0
    ],
    "bounding_box": [
      0,
      0
    ],
    "ocr_score": 0,
    "score": 0,
    "rotation": 0,
    "value": "string"
  },
  "field_12c_col2": {
    "bounding_region": [
      0
    ],
    "bounding_box": [
      0,
      0
    ],
    "ocr_score": 0,
    "score": 0,
    "rotation": 0,
    "value": 0
  },
  "field_12d_col1": {
    "bounding_region": [
      0
    ],
    "bounding_box": [
      0,
      0
    ],
    "ocr_score": 0,
    "score": 0,
    "rotation": 0,
    "value": "string"
  },
  "field_12d_col2": {
    "bounding_region": [
      0
    ],
    "bounding_box": [
      0,
      0
    ],
    "ocr_score": 0,
    "score": 0,
    "rotation": 0,
    "value": 0
  },
  "is_13a": {
    "bounding_region": [
      0
    ],
    "bounding_box": [
      0,
      0
    ],
    "ocr_score": 0,
    "score": 0,
    "rotation": 0,
    "value": true
  },
  "is_13b": {
    "bounding_region": [
      0
    ],
    "bounding_box": [
      0,
      0
    ],
    "ocr_score": 0,
    "score": 0,
    "rotation": 0,
    "value": true
  },
  "is_13c": {
    "bounding_region": [
      0
    ],
    "bounding_box": [
      0,
      0
    ],
    "ocr_score": 0,
    "score": 0,
    "rotation": 0,
    "value": true
  },
  "states": [
    {
      "state": {
        "bounding_region": [
          0
        ],
        "bounding_box": [
          0,
          0
        ],
        "ocr_score": 0,
        "score": 0,
        "rotation": 0,
        "value": "string"
      },
      "employer_state_id": {
        "bounding_region": [
          0
        ],
        "bounding_box": [
          0,
          0
        ],
        "ocr_score": 0,
        "score": 0,
        "rotation": 0,
        "value": "string"
      },
      "state_wages_tips": {
        "bounding_region": [
          0
        ],
        "bounding_box": [
          0,
          0
        ],
        "ocr_score": 0,
        "score": 0,
        "rotation": 0,
        "value": 0
      },
      "state_income_tax": {
        "bounding_region": [
          0
        ],
        "bounding_box": [
          0,
          0
        ],
        "ocr_score": 0,
        "score": 0,
        "rotation": 0,
        "value": 0
      },
      "local_wages_tips": {
        "bounding_region": [
          0
        ],
        "bounding_box": [
          0,
          0
        ],
        "ocr_score": 0,
        "score": 0,
        "rotation": 0,
        "value": 0
      },
      "local_income_tax": {
        "bounding_region": [
          0
        ],
        "bounding_box": [
          0,
          0
        ],
        "ocr_score": 0,
        "score": 0,
        "rotation": 0,
        "value": 0
      },
      "locality_name": {
        "bounding_region": [
          0
        ],
        "bounding_box": [
          0,
          0
        ],
        "ocr_score": 0,
        "score": 0,
        "rotation": 0,
        "value": "string"
      }
    }
  ],
  "field_14_other": [
    {
      "column_1": {
        "bounding_region": [
          0
        ],
        "bounding_box": [
          0,
          0
        ],
        "ocr_score": 0,
        "score": 0,
        "rotation": 0,
        "value": "string"
      },
      "column_2": {
        "bounding_region": [
          0
        ],
        "bounding_box": [
          0,
          0
        ],
        "ocr_score": 0,
        "score": 0,
        "rotation": 0,
        "value": 0
      }
    }
  ]
}

400

User error

application/json

Schema

Schema

oneOf

MALFORMED_PARAMETERS

status string

Default value: fail

error string

Default value: Malformed parameters

details undefined[]

Default value: [object Object]

Example (from schema)

{}

403

User error

application/json

Schema

Schema

oneOf

AUTHENTICATION_CREDENTIALS_WERE_NOT_PROVIDED

status string

Default value: fail

error string

Default value: Authentication credentials were not provided.

Example (from schema)

{}

404

Not found

application/json

Schema

Schema

oneOf

NOT_FOUND

status string

Default value: fail

error string

Default value: Not found.

DOCUMENT_NOT_FOUND

status string

Default value: fail

error string

Default value: Document Not Found

Example (from schema)

{}

429

Rate limit

application/json

Schema

Schema

oneOf

YOU_HAVE_BEEN_RATE_LIMITED

status string

Default value: fail

error string

Default value: You have been rate limited

details undefined[]

Default value: [object Object]

Example (from schema)

{}

499

User error

application/json

Schema

Schema

oneOf

CLIENT_CLOSED_REQUEST_OR_LOST_CONNECTION

status string

Default value: fail

error string

Default value: Client closed request or lost connection

Example (from schema)

{}

503

Service is temporarily unavailable

application/json

Schema

Schema

oneOf

SERVICE_IS_TEMPORARILY_UNAVAILABLE_PLEASE_TRY_AGAIN_LATER

status string

Default value: fail

error string

Default value: Service is temporarily unavailable. Please try again later

Example (from schema)

{}

504

Gateway timeout. Returned if request takes more than 150 seconds. The request might finish successfully later.

application/json

Schema

Schema

oneOf

GATEWAY_TIMEOUT

status string

Default value: fail

error string

Default value: Gateway timeout

Example (from schema)

{}

default

OperationStatus

application/json

Schema

Schema

status string

Default value: fail

error stringrequired
details object[]

Example (from schema)

{
  "status": "fail",
  "error": "string",
  "details": [
    {}
  ]
}

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