Zendesk Collection

SearchBlox provides a Zendesk Collection that allows you to index content from Zendesk, including help center articles and support knowledge base content. It securely connects to your Zendesk account and crawls the available content for indexing. Once indexed, the information becomes searchable within the SearchBlox platform. This helps organizations quickly find and manage support documentation stored in Zendesk.

Creating a Zendesk Collection

You can create a ZendeskCollection by following these steps:

• Log in to the Admin Console, go to the Collections tab, and click Create or the “+” icon.

• Select Zendesk Collection as the collection type.

• Enter a unique name for the collection. The name must contain 3–36 alphanumeric characters, and only underscores (_) are allowed.

• Enable or disable RAG (Retrieval Augmented Generation) depending on your requirement. Enable it if the collection will be used for AI-powered search or chatbot responses.

• Enable Knowledge Graph if you want SearchBlox to extract entities and relationships from the documents in the collection.

• Choose whether the collection should be Private or Public. Enable Private Collection Access to restrict the collection to authenticated users only.

• Configure Collection Encryption if you want to encrypt document content or specific metadata fields.

• Select the Collection Language based on the language used in the documents. The default language is English.

• Click Create to create the Zendesk Collection.

• After the collection is created, you will be redirected to the Zendesk Settings / Authentication section to configure the connection and access details.

Configuring Zendesk Settings

To configure Zendesk integration for your collection, follow these steps:

1. Go to the Zendesk Settings tab within the collection.

2. Enter the Subdomain.
   Provide your Zendesk subdomain (e.g., your-company for your-company.zendesk.com) used to access your Zendesk account.

3. Enter the Email.
   Specify the email address associated with your Zendesk admin account for authentication.

4. Enter the API Token.
   Provide the Zendesk API token generated from your Zendesk account. This is used for secure access to Zendesk data.

5. Enable Index Articles.
   Toggle this option to YES if you want to crawl and index Help Center articles from Zendesk.

6. Enable Index Tickets.
   Toggle this option to YES if you want to crawl and index support tickets. Set to NO if ticket data should not be included.

7. Click Save to store the configuration and enable the system to crawl and index content from your Zendesk account.

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Schedule and Index

Sets the frequency and the start date/time for indexing a collection. Schedule Frequency supported in SearchBlox is as follows:

• Once
• Hourly
• Daily
• Every 48 Hours
• Every 96 Hours
• Weekly
• Monthly

The following operation can be performed in Azure blob collections

Manage Documents Tab

• Using Manage Documents tab we can do the following operations:

  1. Filter
  2. View content
  3. View metadata
  4. Refresh
  5. Delete

• To delete a file from your collection, enter the file path and click "Delete".

• To see the status of an indexed file, click "View Metadata".

Data Fields Tab

Using Data Fields tab we can create custom fields for search and we can see the Default Data Fields with non-encrypted collection. SearchBlox supports 4 types of Data Fields as listed below:

Keyword
Number
Date
Text

• Once the Data fields are configured, collection must be cleared and re-indexed to take effect.

Zendesk Collection Models

The Models page allows you to configure and override AI models used for embeddings, reranking, and LLM-based features within the collection.

Embedding

• Provider specifies the embedding provider used to generate vector representations of documents.
• Model defines the embedding model used to convert document content into vectors for semantic search.

Reranker

• Provider specifies the reranker provider used for improving search result relevance.
• Model defines the reranker model used to re-score and reorder search results based on relevance.

LLM

• Provider specifies the Large Language Model provider used for AI-powered features.

• Model defines the LLM used for tasks such as document enrichment, summaries, and SmartFAQs.

• These settings override global configurations and apply only to the current collection.