検索：look-up-data-table

When you send a document to the pipeline, akaBot Vision will immediately start to extract the data

of the screen. Clicking this button will bring up a Document editing screen where you will see the list

splitting suggestions available in the app. Table Of Content

the data from it. == **Description** == (% class="wikigeneratedid" %) During this stage, the document has an importing status. (% style="text-align:center" %) [[[[image:image-20220420191058-1.png||data-xwiki-image

" %) [[[[image:image-20220420191111-2.png||data-xwiki-image-style-alignment="center"]]>>attach:image-20220420191111-2

on: Built-in checks – we perform Data Integrity checks based on values found on the document. Such checks

the Extraction schema you should be seeing the message for the required fields with no captured value. Table

Customizing Data Extract

– we perform Data Integrity checks based on values found on the document. Such checks could

value. ))) ))) ))) (% class="akb-toc" %) ((( (% class="akb-toc-title" %) ((( Table of Content

Each Pipeline defines the structure of Data fields that akaBot Vision extracts. Description When editing this structure you have two options: Use pre-trained Data fields – AkaBot Vision’s Generic AI engine has been pre-trained to recognize specific Data fields and enables you to start extracting data

[3] Configure Fields for Data Extraction

Customizing Data Extract

Configuring Fields for Data Extraction

** == Using pre-trained Data fields is simple. This function works out of the box and is easy to set up

="wikigeneratedid" id="HParagraph1" %) Each Pipeline defines the structure of Data fields that akaBot Vision

options: * Use pre-trained Data fields – AkaBot Vision’s Generic AI engine has been pre-trained

. Adding a new table In order to create a new table, click [Add Field], select Data Type = “table

A basic element in the extraction schema is the data field. However, akaBot Vision enables the capture of even more complex structures like tables. Adding a predefined table field If you are missing

[4] Capture Custom Table Data

Capturing Custom Table Data in akaBot Vision

Customizing Data Extract

, click [Add Field], select Data Type = “table” and then input the value you want to create a new table

="wikigeneratedid" id="HParagraph1" %) A basic element in the extraction schema is the data field. However, akaBot Vision enables the capture of even more complex structures like tables. == **Adding a predefined table

to a pipeline that has Automation Type is Confident, then export them and change the status. Table

. (% style="text-align:center" %) [[image:image-20220420200751-2.png||cursorshover="true" data-xwiki-image

||cursorshover="true"]] ))) (% class="akb-toc" %) ((( (% class="akb-toc-title" %) ((( Table of Content

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

that you agree with akaBot Vision Terms & Conditions. Step 3: Click Sign up Note: You can register

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

test to prod environment in the future. Setting up production and test environment When you register

pipelines or move pipelines between PipelineGroupgroups easily. Data integrity controls Users will access

any features you need in Test, with your Customer Success Manager. You can easily set up the same

in the future. == **Setting up production and test environment** == When you register an account at **http

or move pipelines between PipelineGroupgroups easily. |Data integrity controls|Users will access

any features you need in Test, with your Customer Success Manager.|You can easily set up the same

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

. Table TAB – move between fields in the direction from the beginning of a row to its end. UP, DOWN

After importing the document successfully and the data extraction process is successfully finished

, akaBot Vision provides users with the capability to add or remove rows in a table To insert a row, you

="wikigeneratedid" %) After importing the document successfully and the data extraction process is successfully

with this status in the “To review” tab in the user interface. [[image:image-20220420193327-1.png||data-xwiki

in each field that has been detected incorrectly [[image:image-20220420193327-2.png||data-xwiki-image

e.g. akaBot Studio) Once you upload the document, it will end up in a particular Tenant and pipeline

of the same pipeline. Table of Content

(via e.g. akaBot Studio) Once you upload the document, it will end up in a particular Tenant

" %) ((( Table of Content ))) {{toc depth="4" start="2"/}} ))) )))