Saved Search Tools in NetSuite for AI Integration

Access and run saved searches in NetSuite through AI client tools. Learn about the available capabilities and permission requirements.

·3 min read·View Oracle Docs

The saved search tools in NetSuite allow users to access and execute saved searches directly from their AI client. This integration enhances the efficiency and flexibility of data retrieval, enabling you to gain insights quickly from your existing saved searches.

What Are Saved Search Tools?

Saved search tools are components that enable you to manage saved searches within NetSuite’s AI framework. The functionality includes:

  • Listing Saved Searches: Use the saved search tool to display all saved searches available in your NetSuite account. This includes details like the saved search ID, title, record type, and its public setting.
  • Running Saved Searches: This tool allows execution of existing saved searches, providing users with the ability to fetch data by running predefined queries.

Tool Descriptions

Listing Saved Searches

The listing tool is identified in the documentation as ns_listSavedSearches. It helps retrieve a wide range of saved searches and includes functionalities such as:

  • Filter by Name: Users can filter saved searches based on their names.

Properties:

PropertyTypeRequired or OptionalDescription
querystringOptionalQuery to filter the results of the saved search.

Running Saved Searches

The end point for running a saved search is noted as ns_runSavedSearch. This tool provides the ability to execute a specified saved search. The key requirements are:

  • Saved Search ID: Required parameter indicating the ID of the saved search to execute.
  • Search Type: This can be required if the saved search uses a standalone search type; otherwise, it is optional.

Properties:

PropertyTypeRequired or OptionalDescription
searchIdstringRequiredThe ID of the saved search.
typestringRequired (if standalone search)The search type of the saved search to load.
range_startnumberOptionalLower bound of the range of search results.
range_endnumberOptionalUpper bound of the range of search results.

Permissions Required

To access the saved search tools in the AI client, users must possess the following permission:

  • Permission ID: LIST_FIND
  • Permission Name: Perform Search
  • Permission Level: View

Who Should Use These Tools?

The saved search tools are particularly useful for developers and administrators who need to interact with saved searches programmatically or through an AI interface. Proper permissions are required for visibility and execution of these tools.

Key Takeaways

  • The saved search tools allow users to list and run saved searches from the AI client.
  • The ns_listSavedSearches and ns_runSavedSearch commands are essential for accessing these features.
  • Permission requirements must be met to utilize these tools effectively.

Source: This article is based on Oracle's official NetSuite documentation.

Frequently Asked Questions (4)

Do I need specific permissions to use the saved search tools in NetSuite via AI integration?
Yes, you must have the `LIST_FIND` permission at the view level to access and use saved search tools through the AI client.
How can I filter saved searches by name using the `ns_listSavedSearches` tool?
You can filter saved searches using the `query` property, which is an optional string parameter to refine your search results based on the saved search name.
Is the search type parameter always required when running a saved search using `ns_runSavedSearch`?
The `type` parameter is only required if your saved search uses a standalone search type. Otherwise, it is optional.
Can I retrieve only a specific range of search results when using `ns_runSavedSearch`?
Yes, you can specify a range of results to retrieve by using the optional `range_start` and `range_end` properties, which define the lower and upper bounds of the desired search results range.
Source: Saved Search Tools Oracle NetSuite Help Center. This article was generated from official Oracle documentation and enriched with additional context and best practices.

Was this article helpful?

More in Integration

View all Integration articles →