Freshworks
The Fresh Connector supports the ingestion of Users and User Profiles. This page describes the steps and configurations needed to ingest these entities from Fresh’s external system. Keep in mind the most basic distinction in Fresh: Agents and Requesters.
By default, a new Fresh Data Source is configured to fetch Requesters.
User Learning
Requesters
Agents
User Field Mappings for Agents
User Profile Learning
Requesters
Agents
Knowledge Learning
Ingest all the KBs from Freshworks
Create an Integration
Go to Settings> Integration > New Integration.
Provide the following details:
Name: Name of the integration
Endpoint: Provide the URL you need to connect to
Public: Determines whether the integration can be used outside the firewall
Description: Enter the description (Optional)
Click Next.
Enter the Authentication details
There is only one type of Authentication supported - Basic.
Basic
Enter your Aisera Service User Name and Password.
Click OK.
Create a Freshworks Data Source
Click Settings > Data Source.
Click + New Data Source and search for Freshworks.
Select the Freshworks Icon and click Next.
Enter the General Details and click Next:
Name
Description
Name
Name of the Data Source
Type
Select the Type: Downstream or Upstream
Integration
Select the Integration created in the step above
Functions
Select one or more of the “Functions” for which this Data Source will be used i.e Knowledge Base Learning, User Learning..etc
Schedule
Select the schedule of the DS you want it to run.
Description
Optional Description can be added
Enter the Configuration details:
Event Type: N/A
Bypass Test Connection: Disable if you want to bypass the test connection
Custom Query: Enter the valid Freshworks query. I.e. the filter that you want to apply interest only to a specific set of records.
Transformation Script: Enter the transformation script if you want to manipulate or transform the data being ingested from the Fresh.
Click Next.
The override section is covered in the 4.2 section below to ingest Agents. (Other configuration details are not needed)
Go to the Data Source you just created and Click Play to Run the Data Source job. (Please refer to the following sections before running the data source job).
User Learning
Requesters
When creating a Fresh Datasource with the “Learn Users” function, by default it is configured to fetch Requesters from the external system and map them into User entities. The mappings are loaded by default and are ready to be used.
Agents
In order to fetch Agents from the external system, you need to configure the Override Configuration field in the Datasource config. Ask your Aisera Team to review internal documentation and add the JSON file using the question mark syntax.
User Field Mappings for Agents
The email-related field mapping needs to be changed for Agents to “email” (from “primary_email”)
User Profile Learning
To ingest User Profiles, we also need to ingest Users. This means that we must choose both “Learn Users” and “Learn User Profiles”. Choosing only the latter will prevent the entries from being properly stored in the database.
Requesters
Fresh Data Sources are configured by default to ingest Requesters. However, there is a specific field mapping that needs to be deleted:
This field mapping (userProfileRoleName) is designed to indicate that a User Learning entry is an agent. You can either change the fixed value or delete it if it is not needed. These are the proposed field mappings for requester user profiles:
Agents
To ingest Agents as User Profiles, you need to use the same JSON Override Configuration as you did for Agent User entries. Ask your Aisera Team to add the JSON file using the question mark syntax.
You also need to change the field mappings that reference the email as an external field path. The name of the “primary_email” field needs to be changed into “email”
These are the proposed field mappings for Agent User Profile entries:
Learn KBs with ACL Tags
Documents in Freshworks can contain various attributes that are related to the ACL mechanism.
By default, the Freshworks connector does not ingest tags connected to visibility. You need to use Override configs in a Data Source configuration. See your Aisera Team to add the JSON file.
Review Crawled Knowledge Documents
After the Data Source run completes, the administrator may review all the knowledge documents and ingested sections.
To view all the ingested documents:
Navigate to AI Workbench on the left-hand main navigation panel.
Click the Review > Knowledge Review tab at the top of the page, as shown below:
You will see “Commit Reviewed” and the number of documents that are ingested.
Since this is the first crawl, all the documents are “Reviewed” by default (Refer to the Knowledge Management document for more details)
Click on Commit Reviewed and click Commit.
Now, click on the Knowledge Tab in the left panel and you will see all the ingested documents. (It might take a couple of minutes to show/load the docs in the knowledge tab)
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