ServiceNow Collection

A ServiceNow Collection connects SearchBlox to your ServiceNow instance so that knowledge base articles, support documentation, and other ServiceNow content can be indexed and searched through SearchBlox.

Once set up, users can search ServiceNow content directly from your SearchBlox search interface — without logging in to ServiceNow separately.

Before You Begin:

You will need a ServiceNow instance URL (e.g. https://your-instance.service-now.com)
A ServiceNow username and password with API access permissions
Your preferred authentication method: Basic Auth or OAuth2 (Password Grant)

Creating a ServiceNow Collection

You can create a ServiceNow Collection by following these steps:

Log in to the Admin Console, go to the Collections tab, and click Create or the “+” icon.
Select ServiceNow 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 ServiceNow Collection.
After the collection is created, you will be redirected to the ServiceNow Settings / Authentication section to configure the connection and access details.

Configuring ServiceNow Settings

To configure ServiceNow for your collection, follow these steps:

Go to the ServiceNow Settings tab within the collection.
Enter the Instance URL.
Provide your ServiceNow instance URL (e.g., https://your-instance.service-now.com).
Select the Authentication Type.
Choose between Basic Auth or OAuth2 (Password Grant) based on your setup.
Enter the Username.
Provide the ServiceNow username used for API access.
Enter the Password.
Provide the password for the specified ServiceNow user.
Click Test Connection to verify that the credentials are valid and the connection is successful.
Click Save Credentials to store the configuration and enable SearchBlox to connect to your ServiceNow instance.

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

Activity	Description
Enable Scheduler for Indexing	Once enabled, you can set the Start Date and Frequency
Schedule	For each collection, indexing can be scheduled based on the above options.
View all Schedules	Redirects to the Schedules section, where all the Collection Schedules are listed.

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:

Type	Description
Keyword	Used for alphanumeric values such as IDs, tags, codes, or other exact-match fields.
Number	Used for numeric values such as prices, quantities, ratings, or counts.
Date	Used for date values that can be searched, sorted, and filtered.
Text	Used for full-text search within custom field content.

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

Servicenow 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.