Search: extract-structured-data

Attach Browser (NB) Check/Uncheck (NB) Click (NB) Close Tab (NB) Element Exist (NB) Extract Structured Data (NB) Get Element (NB) Get Text (NB) Get Web Attribute (NB) Go Back (NB) Go Forward (NB) Hover (NB) Inject JavaScript (NB) Navigate To (NB) Open Browser (NB) Quit Browser (NB) Refresh (NB

/Activities/Element%20Exist%20%28NB%29/]] * [[Extract Structured Data (NB)>>url:https://docs.akabot.com/bin/view/Activities/Native%20Browser/Activities/Extract%20Structured%20Data%20%28NB%29/]] * [[Get Element

1. Create an Account Note: Although akaBot Vision currently supports Pre-trained data fields only for Invoice processing, the technology is documented agnostic and can extract data from any structured document including receipts, purchase orders, shipping documents, etc. Please contact support

currently supports Pre-trained data fields only for Invoice processing, the technology is documented agnostic and can extract data from any structured document including receipts, purchase orders, shipping

-20220420182302-1.png||alt="image-20220420183141-4.png" data-xwiki-image-style-alignment="center"]] **Step 2

Automation of Fields Capture Custom Table Data Configure Automation Type for Pipeline Configure Fields for Data Extraction

[6] Customize Data Extract

Customizing Data Extract

/Configure%20Automation%20Type%20for%20Pipeline%20/]] * [[Configure Fields for Data Extraction>>path:/bin

* [[Automation of Fields>>path:/bin/view/akaBot%20Vision/Customizing%20Data%20Extract/Automation%20of%20Fields%20in%20akaBot%20Vision/]] * [[Capture Custom Table Data>>path:/bin/view/akaBot%20Vision

extracting the data fields. The AI extraction typically takes up to 5 seconds for 1 A4 page. After

]] [[image:image-20220420184331-2.png||data-xwiki-image-style-alignment="center"]] Click “OK” and the AI will automatically begin extracting the data fields. The AI extraction typically takes up to 5 seconds for 1 A4 page. [[image:image-20220420184331-3.png||data-xwiki-image-style-alignment="center"]] After processing

The XML Activities Pack contains activities that enable you to manipulate XML files, such as deserializing documents so that data extraction is easier. See also: Release Notes Activities

(% class="akb-page-with-toc" %) ((( (% class="akb-page-content" %) ((( (% class="box" %) ((( The **XML Activities Pack** contains activities that enable you to manipulate XML files, such as deserializing documents so that data extraction is easier. ))) See also: * [[Release Notes>>path:/bin

The DataTable Activities belongs to Core Activities Pack. It contains several activities that enable the robots to manipulate data tables by adding or extracting information. See also: Release Notes Activities

Data Table

Data Table

the robots to manipulate data tables by adding or extracting information. ))) See also: * [[Release Notes>>path:/bin/view/Activities/Data%20Table/%5B1%5D%20Release%20Notes/]] * [[Activities>>path:/bin/view/Activities/Data%20Table/Activities/]] ))) )))

The XML Activities Pack contains activities that enable you to manipulate XML files, such as executing XPath queries and deserializing documents, so that data extraction is easier. See also: Release Notes Activities

(% class="akb-page-with-toc" %) ((( (% class="akb-page-content" %) ((( (% class="box" %) ((( The **XML Activities Pack** contains activities that enable you to manipulate XML files, such as executing XPath queries and deserializing documents, so that data extraction is easier. ))) See also

documents to extract data. Staff can create a new learning model by following these below steps: Step 1

in documents. This helps the model will extract data more exactly. Staff can choose "Label" or "Value

. After training models successfully, staff can use that model to extract data by creating new pipeline

, send the learning models to production and use them to run on actual documents to extract data. Staff

" for each field if having enough data in documents. This helps the model will extract data more exactly

successfully, staff can use that model to extract data by creating new pipeline with document type is the model

the output data generated by the activities. The Python Scope container activity connects to the Python

. The PythonObject variable is specially designed to handle and manipulate Python data. By using the Load Python

to a PythonObject and you can also convert it to a .NET data type by using the Get Python Object activity

as retrieve the output data generated by the activities. The Python Scope container activity connects

and manipulate Python data. By using the Load Python Script activity, you can easily assign the code from any

convert it to a .NET data type by using the Get Python Object activity. With this powerful variable

, or human will download IDP output and then use that structured data to input to other enterprise systems

Vision will automatically send a response containing documentId information, document Path, and extracted data to the user's server by API Output Note: Most of the APIs in akaBot Vision are synchronous APIs

and then use that structured data to input to other enterprise systems. **Step 3**: IDP system will inform

will automatically send a response containing documentId information, document Path, and extracted data to the user's