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Document Intelligence add-on capabilities

Important

  • Document Intelligence public preview releases provide early access to features that are in active development. Features, approaches, and processes may change, prior to General Availability (GA), based on user feedback.
  • The public preview version of Document Intelligence client libraries default to REST API version 2024-07-31-preview.
  • Public preview version 2024-07-31-preview is currently only available in the following Azure regions. Note that the custom generative (document field extraction) model in AI Studio is only available in North Central US region:
    • East US
    • West US2
    • West Europe
    • North Central US

This content applies to: checkmark v4.0 (preview) | Previous versions: blue-checkmark v3.1 (GA)

This content applies to: checkmark v3.1 (GA) | Latest version: purple-checkmark v4.0 (preview)

Note

Add-on capabilities are available within all models except for the Business card model.

Capabilities

Document Intelligence supports more sophisticated and modular analysis capabilities. Use the add-on features to extend the results to include more features extracted from your documents. Some add-on features incur an extra cost. These optional features can be enabled and disabled depending on the scenario of the document extraction. To enable a feature, add the associated feature name to the features query string property. You can enable more than one add-on feature on a request by providing a comma-separated list of features. The following add-on capabilities are available for 2023-07-31 (GA) and later releases.

For 2024-07-31-preview release and later, the Read model supports searchable PDF output:

Note

  • Not all add-on capabilities are supported by all models. For more information, see model data extraction.

  • Add-on capabilities are currently not supported for Microsoft Office file types.

Document Intelligence supports optional features that can be enabled and disabled depending on the document extraction scenario. The following add-on capabilities are available for 2023-10-31-preview, and later releases:

Note

The query fields implementation in the 2023-10-30-preview API is different from the last preview release. The new implementation is less expensive and works well with structured documents.

Version availability

Add-on Capability Add-On/Free 2024-02-29-preview 2023-07-31 (GA) 2022-08-31 (GA) v2.1 (GA)
Font property extraction Add-On ✔️ ✔️ n/a n/a
Formula extraction Add-On ✔️ ✔️ n/a n/a
High resolution extraction Add-On ✔️ ✔️ n/a n/a
Barcode extraction Free ✔️ ✔️ n/a n/a
Language detection Free ✔️ ✔️ n/a n/a
Key value pairs Free ✔️ n/a n/a n/a
Query fields Add-On* ✔️ n/a n/a n/a

✱ Add-On - Query fields are priced differently than the other add-on features. See pricing for details.

Supported file formats

  • PDF

  • Images: JPEG/JPG, PNG, BMP, TIFF, HEIF

✱ Microsoft Office files are currently not supported.

High resolution extraction

The task of recognizing small text from large-size documents, like engineering drawings, is a challenge. Often the text is mixed with other graphical elements and has varying fonts, sizes, and orientations. Moreover, the text can be broken into separate parts or connected with other symbols. Document Intelligence now supports extracting content from these types of documents with the ocr.highResolution capability. You get improved quality of content extraction from A1/A2/A3 documents by enabling this add-on capability.

{your-resource-endpoint}.cognitiveservices.azure.com/documentintelligence/documentModels/prebuilt-layout:analyze?api-version=2024-02-29-preview&features=ocrHighResolution
{your-resource-endpoint}.cognitiveservices.azure.com/formrecognizer/documentModels/prebuilt-layout:analyze?api-version=2023-07-31&features=ocrHighResolution

Formula extraction

The ocr.formula capability extracts all identified formulas, such as mathematical equations, in the formulas collection as a top level object under content. Inside content, detected formulas are represented as :formula:. Each entry in this collection represents a formula that includes the formula type as inline or display, and its LaTeX representation as value along with its polygon coordinates. Initially, formulas appear at the end of each page.

Note

The confidence score is hard-coded.

{your-resource-endpoint}.cognitiveservices.azure.com/documentintelligence/documentModels/prebuilt-layout:analyze?api-version=2024-02-29-preview&features=formulas
{your-resource-endpoint}.cognitiveservices.azure.com/formrecognizer/documentModels/prebuilt-layout:analyze?api-version=2023-07-31&features=formulas

Font property extraction

The ocr.font capability extracts all font properties of text extracted in the styles collection as a top-level object under content. Each style object specifies a single font property, the text span it applies to, and its corresponding confidence score. The existing style property is extended with more font properties such as similarFontFamily for the font of the text, fontStyle for styles such as italic and normal, fontWeight for bold or normal, color for color of the text, and backgroundColor for color of the text bounding box.

  {your-resource-endpoint}.cognitiveservices.azure.com/documentintelligence/documentModels/prebuilt-layout:analyze?api-version=2024-02-29-preview&features=styleFont
  {your-resource-endpoint}.cognitiveservices.azure.com/formrecognizer/documentModels/prebuilt-layout:analyze?api-version=2023-07-31&features=styleFont

Barcode property extraction

The ocr.barcode capability extracts all identified barcodes in the barcodes collection as a top level object under content. Inside the content, detected barcodes are represented as :barcode:. Each entry in this collection represents a barcode and includes the barcode type as kind and the embedded barcode content as value along with its polygon coordinates. Initially, barcodes appear at the end of each page. The confidence is hard-coded for as 1.

Supported barcode types

Barcode Type Example
QR Code Screenshot of the QR Code.
Code 39 Screenshot of the Code 39.
Code 93 Screenshot of the Code 93.
Code 128 Screenshot of the Code 128.
UPC (UPC-A & UPC-E) Screenshot of the UPC.
PDF417 Screenshot of the PDF417.
EAN-8 Screenshot of the European-article-number barcode ean-8.
EAN-13 Screenshot of the European-article-number barcode ean-13.
Codabar Screenshot of the Codabar.
Databar Screenshot of the Data bar.
Databar Expanded Screenshot of the Data bar Expanded.
ITF Screenshot of the interleaved-two-of-five barcode (ITF).
Data Matrix Screenshot of the Data Matrix.
{your-resource-endpoint}.cognitiveservices.azure.com/documentintelligence/documentModels/prebuilt-layout:analyze?api-version=2024-02-29-preview&features=barcodes
{your-resource-endpoint}.cognitiveservices.azure.com/formrecognizer/documentModels/prebuilt-layout:analyze?api-version=2023-07-31&features=barcodes

Language detection

Adding the languages feature to the analyzeResult request predicts the detected primary language for each text line along with the confidence in the languages collection under analyzeResult.

{your-resource-endpoint}.cognitiveservices.azure.com/documentintelligence/documentModels/prebuilt-layout:analyze?api-version=2024-02-29-preview&features=languages
{your-resource-endpoint}.cognitiveservices.azure.com/formrecognizer/documentModels/prebuilt-layout:analyze?api-version=2023-07-31&features=languages

Searchable PDF

The searchable PDF capability enables you to convert an analog PDF, such as scanned-image PDF files, to a PDF with embedded text. The embedded text enables deep text search within the PDF's extracted content by overlaying the detected text entities on top of the image files.

Important

  • Currently, the searchable PDF capability is only supported by Read OCR model prebuilt-read. When using this feature, please specify the modelId as prebuilt-read, as other model types will return error for this preview version.
  • Searchable PDF is included with the 2024-07-31-preview prebuilt-read model with no usage cost for general PDF consumption.

Use searchable PDF

To use searchable PDF, make a POST request using the Analyze operation and specify the output format as pdf:


POST /documentModels/prebuilt-read:analyze?output=pdf
{...}
202

Once the Analyze operation is complete, make a GET request to retrieve the Analyze operation results.

Upon successful completion, the PDF can be retrieved and downloaded as application/pdf. This operation allows direct downloading of the embedded text form of PDF instead of Base64-encoded JSON.


// Monitor the operation until completion.
GET /documentModels/prebuilt-read/analyzeResults/{resultId}
200
{...}

// Upon successful completion, retrieve the PDF as application/pdf.
GET /documentModels/prebuilt-read/analyzeResults/{resultId}/pdf
200 OK
Content-Type: application/pdf

Key-value Pairs

In earlier API versions, the prebuilt-document model extracted key-value pairs from forms and documents. With the addition of the keyValuePairs feature to prebuilt-layout, the layout model now produces the same results.

Key-value pairs are specific spans within the document that identify a label or key and its associated response or value. In a structured form, these pairs could be the label and the value the user entered for that field. In an unstructured document, they could be the date a contract was executed on based on the text in a paragraph. The AI model is trained to extract identifiable keys and values based on a wide variety of document types, formats, and structures.

Keys can also exist in isolation when the model detects that a key exists, with no associated value or when processing optional fields. For example, a middle name field can be left blank on a form in some instances. Key-value pairs are spans of text contained in the document. For documents where the same value is described in different ways, for example, customer/user, the associated key is either customer or user (based on context).

REST API

{your-resource-endpoint}.cognitiveservices.azure.com/documentintelligence/documentModels/prebuilt-layout:analyze?api-version=2024-02-29-preview&features=keyValuePairs

Query Fields

Query fields are an add-on capability to extend the schema extracted from any prebuilt model or define a specific key name when the key name is variable. To use query fields, set the features to queryFields and provide a comma-separated list of field names in the queryFields property.

  • Document Intelligence now supports query field extractions. With query field extraction, you can add fields to the extraction process using a query request without the need for added training.

  • Use query fields when you need to extend the schema of a prebuilt or custom model or need to extract a few fields with the output of layout.

  • Query fields are a premium add-on capability. For best results, define the fields you want to extract using camel case or Pascal case field names for multi-word field names.

  • Query fields support a maximum of 20 fields per request. If the document contains a value for the field, the field and value are returned.

  • This release has a new implementation of the query fields capability that is priced lower than the earlier implementation and should be validated.

Note

Document Intelligence Studio query field extraction is currently available with the Layout and Prebuilt models 2024-02-29-preview 2023-10-31-preview API and later releases except for the US tax models (W2, 1098s, and 1099s models).

Query field extraction

For query field extraction, specify the fields you want to extract and Document Intelligence analyzes the document accordingly. Here's an example:

  • If you're processing a contract in the Document Intelligence Studio, use the 2024-02-29-preview or 2023-10-31-preview versions:

    Screenshot of the query fields button in Document Intelligence Studio.

  • You can pass a list of field labels like Party1, Party2, TermsOfUse, PaymentTerms, PaymentDate, and TermEndDate as part of the analyze document request.

    Screenshot of query fields selection window in Document Intelligence Studio.

  • Document Intelligence is able to analyze and extract the field data and return the values in a structured JSON output.

  • In addition to the query fields, the response includes text, tables, selection marks, and other relevant data.

{your-resource-endpoint}.cognitiveservices.azure.com/documentintelligence/documentModels/prebuilt-layout:analyze?api-version=2024-02-29-preview&features=queryFields&queryFields=TERMS

Next steps

Learn more: Read model Layout model

SDK samples: python

Find more samples: Add-on capabilities

Find more samples: Add-on capabilities