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from a human to correct or confirm. Operation Model There are 3 modes to get output from the akaBot

are collected from multiple document sources via RPA bot, API, or human effort then upload to the IDP system

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

. == == == **Operation Model** == There are 3 modes to get output from the akaBot Vision system: 1. **Single Invoice

== [[image:1694170289882-347.png]] == **Step 1 and 2:** Documents are collected from multiple document

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

to the "Confirmed" status and get the extracted data information by calling the API Export Document to IDP Server

: Attribute Type Description aiResponse string Result get from AI checkSum string List documents that want

organization's data and account information. In this document, you will find an introduction to the API usage

|string|Result get from AI |checkSum|string|List documents that want to be uploaded |contentType|string

** == The akaBot Vision API allows you to programmatically access and manage your organization's data and account information. In this document, you will find an introduction to the API usage from a developer perspective

. You can use this key from the import document activity. Extract type: you can choose DataTable/Json

the status. You can check the status on akaBot Vision. Get Documents To get specific documents

to get documents Status: the status you want to get Ex: you can get all Confirmed documents

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

: the ID of the file you want to export. You can use this key from the import document activity. * Extract

if the value is true, otherwise remains the status. You can check the status on akaBot Vision. === **Get

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

with a "welcome popup" displaying some brief instructional information. Please click "Get Started" to start your

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

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

choose base model, this new model will get all the fields that the based model has and staff can add more

choose base model, staff will have to create form fields and table from scratch Step 5: Click "Save

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

, this new model will get all the fields that the based model has and staff can add more fields by clicking

from scratch [[image:image-20230213141914-5.png||cursorshover="true"]] (% class="box infomessage

User can receive extraction results of documents in akaBot Vision via API Output. By configuring an API to directly connect from akaBot Vision to user's systems, user will get extraction results. In this article, we will show you how to configure API Output Step 1: Go to Pipeline's Configuration Step 2

Get Results Via API Output

Get Results Via API Output

User can receive extraction results of documents in akaBot Vision via API Output. By configuring an API to directly connect from akaBot Vision to user's systems, user will get extraction results

-1419-021 (Ramcharan, Ryan Thomas).pdf",   "pipelineName": "not split never auth",   "data

will be also deleted. Moreover, documents usage data will be deleted from statistics Step 3: Click

data will be deleted from statistics ))) [[image:image-20221019135915-7.png||cursorshover="true

imported to a specific queue or which data fields required the most corrections. The dashboard’s reports

. 6. Average Processing Time This statistic shows the average time that documents are moved from

= Time that documents move from "To-review" status to "Confirmed" status / Total documents 7. Average

to a specific queue or which data fields required the most corrections. The dashboard’s reports could also help

that documents are moved from "To-review" status to "Confirmed" status It will be calculated by the formula: **Average Processing Time = Time that documents move from "To-review" status to "Confirmed" status / Total

: Choose Automation Type and set conditions for required fields and data formats The Automation Type

will be bypassed Bypass wrong data formats: All the documents with wrong data formats inside will be moved

. If you turn this mode on, all the wrong data formats will be bypassed Step 3: Click [Save] to save

Customizing Data Extract

Automation Type and set conditions for required fields and data formats ))) * The Automation Type will have

fields will be bypassed * Bypass wrong data formats: All the documents with wrong data formats inside

these later. If you turn this mode on, all the wrong data formats will be bypassed [[image:image

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

Shortcuts When reviewing documents in akaBot Vision, there are multiple ways of moving between data fields

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

="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