- Overview
- Document Processing Contracts
- Release notes
- About the Document Processing Contracts
- Box Class
- IPersistedActivity interface
- PrettyBoxConverter Class
- IClassifierActivity Interface
- IClassifierCapabilitiesProvider Interface
- ClassifierDocumentType Class
- ClassifierResult Class
- ClassifierCodeActivity Class
- ClassifierNativeActivity Class
- ClassifierAsyncCodeActivity Class
- ClassifierDocumentTypeCapability Class
- ExtractorAsyncCodeActivity Class
- ExtractorCodeActivity Class
- ExtractorDocumentType Class
- ExtractorDocumentTypeCapabilities Class
- ExtractorFieldCapability Class
- ExtractorNativeActivity Class
- ExtractorResult Class
- ICapabilitiesProvider Interface
- IExtractorActivity Interface
- ExtractorPayload Class
- DocumentActionPriority Enum
- DocumentActionData Class
- DocumentActionStatus Enum
- DocumentActionType Enum
- DocumentClassificationActionData Class
- DocumentValidationActionData Class
- UserData Class
- Document Class
- DocumentSplittingResult Class
- DomExtensions Class
- Page Class
- PageSection Class
- Polygon Class
- PolygonConverter Class
- Metadata Class
- WordGroup Class
- Word Class
- ProcessingSource Enum
- ResultsTableCell Class
- ResultsTableValue Class
- ResultsTableColumnInfo Class
- ResultsTable Class
- Rotation Enum
- SectionType Enum
- WordGroupType Enum
- IDocumentTextProjection Interface
- ClassificationResult Class
- ExtractionResult Class
- ResultsDocument Class
- ResultsDocumentBounds Class
- ResultsDataPoint Class
- ResultsValue Class
- ResultsContentReference Class
- ResultsValueTokens Class
- ResultsDerivedField Class
- ResultsDataSource Enum
- ResultConstants Class
- SimpleFieldValue Class
- TableFieldValue Class
- DocumentGroup Class
- DocumentTaxonomy Class
- DocumentType Class
- Field Class
- FieldType Enum
- LanguageInfo Class
- MetadataEntry Class
- TextType Enum
- TypeField Class
- ITrackingActivity Interface
- ITrainableActivity Interface
- ITrainableClassifierActivity Interface
- ITrainableExtractorActivity Interface
- TrainableClassifierAsyncCodeActivity Class
- TrainableClassifierCodeActivity Class
- TrainableClassifierNativeActivity Class
- TrainableExtractorAsyncCodeActivity Class
- TrainableExtractorCodeActivity Class
- TrainableExtractorNativeActivity Class
- Document Understanding Digitizer
- Document Understanding ML
- Document Understanding OCR Local Server
- Document Understanding
- Release notes
- About the Document Understanding activity package
- Project compatibility
- Set PDF Password
- Merge PDFs
- Get PDF Page Count
- Extract PDF Text
- Extract PDF Images
- Extract PDF Page Range
- Extract Document Data
- Extract Document Data - Preview
- Create Validation Task and Wait
- Wait for Validation Task and Resume
- Create Validation Task
- Create Classification Validation Task
- Create Classification Validation Task and Wait
- Wait for Classification Validation Task and Resume
- Intelligent OCR
- Release notes
- About the IntelligentOCR activity package
- Project compatibility
- Configuring Authentication
- Load Taxonomy
- Digitize Document
- Classify Document Scope
- Keyword Based Classifier
- Document Understanding Project Classifier
- Intelligent Keyword Classifier
- Create Document Classification Action
- Wait For Document Classification Action And Resume
- Train Classifiers Scope
- Keyword Based Classifier Trainer
- Intelligent Keyword Classifier Trainer
- Data Extraction Scope
- Document Understanding Project Extractor
- RegEx Based Extractor
- Form Extractor
- Intelligent Form Extractor
- Present Validation Station
- Create Document Validation Action
- Wait For Document Validation Action And Resume
- Train Extractors Scope
- Export Extraction Results
- ML Services
- OCR
- OCR Contracts
- Release notes
- About the OCR Contracts
- Project compatibility
- IOCRActivity Interface
- OCRAsyncCodeActivity Class
- OCRCodeActivity Class
- OCRNativeActivity Class
- Character Class
- OCRResult Class
- Word Class
- FontStyles Enum
- OCRRotation Enum
- OCRCapabilities Class
- OCRScrapeBase Class
- OCRScrapeFactory Class
- ScrapeControlBase Class
- ScrapeEngineUsages Enum
- ScrapeEngineBase
- ScrapeEngineFactory Class
- ScrapeEngineProvider Class
- OmniPage
- PDF
- [Unlisted] Abbyy
- [Unlisted] Abbyy Embedded

Document Understanding Activities
PREVIEWExtract Document Data - Preview
UiPath.IntelligentOCR.StudioWeb.Activities.ExtractDocumentDataWithDocumentData<UiPath.IntelligentOCR.StudioWeb.Activities.DataExtraction.ExtendedExtractionResultForDocumentData>
Extracts data from an input file or Document Data object, and stores the results into a Document Data object.
The Generative Predefined project type and the corresponding extractors are not available in Automation Suite.
Designer panel
- Input - Requires you to
specify the file itself, or Document Data, in case you have used other Document
Understanding Activities before in your workflow, (for example, Classify
Document).
Important: The maximum numbers of pages a file can have is 500. Files exceeding this limit fail to extract.
- Project - Requires you to
select your Document Understanding project from the dropdown list. The available
options are:
- Predefined – Classic project type that uses pre-trained specialized models recommended for standard scenarios.
- Generative Predefined – Modern project type that uses pre-trained generative models accepting instructions as input for extraction of document data.
- Existing projects from the tenant and folder you are connected to.
- You can create a custom
project by going to Document Understanding.
For more information, visit Introduction for building models.
Note: If you have created more than 500 projects on your tenant and use the Extract Document Data activity, UiPath Studio or Studio Web will not display any projects beyond the initial 500. Therefore, those projects cannot be used.
- Extractor - After you
select a project, you can also select an extractor that you want to use.
- For the Predefined
project, you can select a pre-trained model. Visit Out-of-the-box models for a
list of pre-trained models that you can use.
Note: The Extract Document Data activity extracts the information for the fields available on the document type for the selected extractor (regardless of the actual type of the document). This is not applicable for generative models.
- For the Generative
Predefined project, you have three choices for extraction,
tailored to a specific document layout:
- Long Document Simple Layout Extractor – Recommended for long form documents with mostly text and headings. For example, you can use the Long Document Simple Layout Extractor on documents such as lease agreements, master service agreements, or other similar documents.
- Long Document Complex Layout Extractor – Recommended for long form documents that include elements such as images, handwriting, form controls, floating callout boxes, or other complex layout types. For example, you can use the Long Document Complex Layout Extractor on documents such as insurance policies, or other similar documents.
- Short Document Complex Layout Extractor – Recommended for short documents that include elements such as images, handwriting, form control, floating callout boxes, or other complex layout types. For example, you can use the Short Document Complex Layout Extractor on documents such as government IDs, healthcare intake forms, or other similar documents.
- For the Predefined
project, you can select a pre-trained model. Visit Out-of-the-box models for a
list of pre-trained models that you can use.
- Document Type details -
This field appears if you choose the option Generative. Prompt to
identify the fields to be extracted, provided as key-value pairs, where the key
represents the name of the field and the value a description for it, helping the
extractor identify the corresponding value. Select the field, and you will get a
prompt with the following options, provided as pairs:
- Field name - Requires you to input the field name to be extracted (Ex. Due date) (30-character limit)
- Instruction - Requires you to provide instructions about what information should be extracted for the corresponding field.. The maximum number of characters allowed is 1000. The response, extraction result, also called Completion, has a word limit of 700. This is limited to 700 words. This means that you can't extract more than 700 words from a single prompt. If your extraction requirements exceed this limit, you can divide the document into multiple pages, process them individually, and then merge the results afterwards.
Tip: For good practices on how to use generative prompts, check the Generative extractor - Good practices page. - Version or Tag - Use this
property when using an existing Document Understanding modern project. Select
the tag that corresponds to the project version from which you want to process
data. For instance, if you choose the Production tag assigned to Version
3, the activity processes data from Version 3 of your project in the production
environment.
The default value for Version is Staging. If the Staging tag doesn't exist in your selected project, then the default value is Production.
For more information about versions, visit Publishing models.
- Document Type - When you choose a tag from the Version field, the activity automatically selects the first deployed document type from the relevant version of your chosen project. Moreover, the activity shows the extraction fields related to your chosen document type.
Properties panel
Input
- Timeout (seconds) - Maximum execution time (in seconds) for the call to the generative model. If the operation exceeds this timeout, it is automatically terminated to prevent delays or hangs. This property is only displayed if one of the following extractor is selected: Long Document Simple Layout Extractor, Long Document Complex Layout Extractor, or Short Document Complex Layout Extractor.
- Auto-validation - Use this
option to enable automatic validation, a capability that helps validate the
results obtained for data extraction against a Generative model. The default
value for the Auto-validation field is
False
.- Confidence
threshold - This field becomes visible once you enable
Auto-validation. Extraction results falling below the
threshold are compared to the generative extraction model. If they
match, the system adjusts the extraction confidence to meet the
threshold value. Possible threshold values range from 0 to 100.
If the value is set to 0, no validation is applied. However, if you set a specific value (from 0 to 100), the system checks all extraction results below this value. For example, if you set a confidence threshold of 80%, the system will apply the generative validation for fields with confidence below 80%.
Note: Auto-validation is available only for specialized extraction models.
- Confidence
threshold - This field becomes visible once you enable
Auto-validation. Extraction results falling below the
threshold are compared to the generative extraction model. If they
match, the system adjusts the extraction confidence to meet the
threshold value. Possible threshold values range from 0 to 100.
- Generate Data Type - If
set to
True
, indicates that the output should be generated based on the selected extractor, resulting in anIDocumentData<ExtractorType>
object. Alternatively, if set toFalse
, indicates that the data generation should be skipped, resulting in a genericIDocumentData<DictionaryData>
object.Visit Document Data for additional details and limitations available for the two object types.
Output
- Document Data - All the
extracted field data from the file. Information can also be received from
Classify Document.
Visit Document data to learn how Document Data works and how to consume the extracted results for single and multi-value fields.
To quickly get started with the generative capabilities of the Extract Document Data activity, perform the following steps:
- Add an Extract Document Data activity.
- From the Project dropdown list, select Generative Predefined.
- For Extractor, select one of
the following extractors: Long Document Simple Layout Extractor, Long
Document Complex Layout Extractor, or Short Document Complex Layout
Extractor.
The Document Type details property appears in the body of the activity.
- For Dictionary provide your
instructions as Dictionary key-value pairs, where:
- Field name represents
the name of the field that you want to extract from the document. For
example,
email address
. - Instruction represents
the instruction about what information you want to give the extractor for
extracting the field. It is the description used by the generative extractor
to identify the corresponding value.
For example, check the following table for a sample of key-value pairs:
Table 1. Examples of key-value pairs for the generative extractor prompt Field name Instruction Name "What is the name of the candidate?" Current Job "What is the current job of the candidate?" Employer "What is the current employer of the candidate?" Figure 1. Key-value pairs details for the generative extractor
- Field name represents
the name of the field that you want to extract from the document. For
example,