---
sourceDocument: Australia Conversational Interfaces
sourceDocumentLink: https://www.servicenow.com/docs/r/australia/conversational-interfaces

 Release :

    - australia

ft:locale :

    - en-US

ft:publication_title :

    - Australia Conversational Interfaces

ft:clusterId :

    - convint

bundleId :

    - convint

workflow :

    - Platform


---

# Input Collector user input control

# Input Collector user input control {#ariaid-title1}

Release version: Australia  
Updated August 27, 2026  
![](https://www.servicenow.com/docs/portal-asset/ico-clock) 2 minutes to read
Summarize  
![AI sparkle icon](https://servicenow.com/docs/portal-asset/ai-sparkle-icon) Summarized using AI  
This content was generated using new OpenAI-powered functionality. Results are provided on an as is basis and are not guaranteed to be accurate or complete.  

## Summary of Input Collector user input control

The Input Collector control in ServiceNow Otto enables the collection of user data during conversations that utilize large language model (LLM) topic discovery.
It is designed to gather and manage user inputs efficiently within these LLM-driven interactions, enhancing the conversational experience and data accuracy.
Show full answer Show less  

## Key Features

* **Availability:** Only available for topics using LLM discovery.
* **Input Capacity:** Can hold up to 5 LLM user inputs per Input Collector node, excluding other Input Collectors. To exceed this limit, multiple Input Collector nodes can be chained, or the system property `com.glide.cs.vainputcollectormaxnodes` can be adjusted.
* **Node Management:** Users can reorder, add, or remove nodes within an Input Collector using both canvas and table views. Drag-and-drop functionality on the canvas and up/down arrows in the table view facilitate this management.
* **Reprompting:** The number of times the Input Collector reprompts users before initiating a search can be configured via the system property `snvadgenai.inputcollectorrepromptlimit`. The default is 2 prompts, with a minimum of 1. Setting very high values effectively disables automatic searches, allowing extended data collection.
* **Flow Action Properties:** Key properties include:
  * **Node name:** Identifier for the node in the topic flow.
  * **Advanced instructions for LLM:** Customize LLM behavior with additional instructions, scripts, or conditions.
  * **Confirmation message:** Option to display a summary of collected inputs for user confirmation before proceeding, enabled by default.
  * **Conditional visibility and skipping:** Nodes can be conditionally shown or made skippable using no-code conditions or scripts.
* **Channel Support:**
  * Microsoft Teams: Supported without constraints.
  * Slack: Not supported.
  * SMS Twilio: Supported without constraints.
  * WhatsApp: Not supported.
  * Google Chat: Supported without constraints.

## Practical Application for ServiceNow Customers

By leveraging the Input Collector control, customers can efficiently collect multiple user inputs in LLM-driven conversations, customize interaction flows, and control user prompting behavior to improve the quality and completeness of gathered data. The ability to reorder and manage input nodes enhances flexibility in designing conversational topics. The confirmation message feature helps ensure data accuracy by allowing users to review and validate their inputs before proceeding. Understanding channel support helps customers deploy Input Collector-enabled conversations on supported platforms effectively.  
Use the Input Collector control to gather data for use by ServiceNow Otto in conversations that use large language model (LLM) topic discovery.

## Input Collector demonstration {#va-ai-data-collector__section_qyy_lxt_51c}

For an example of the Input Collector from a user perspective, watch this video.

## Input Collector properties {#va-ai-data-collector__section_xwb_mgn_pdb}

The Input Collector is only available for topics that use LLM discovery.

The Input Collector can hold up to 5 of any of the LLM user inputs aside from another Input Collector. To collect more than 5 user inputs, place multiple Input Collector nodes in sequence or adjust the Value of the
com.glide.cs.va_input_collector_max_nodes property in the System Properties \[sys_properties\] table.

You can reorder nodes inside the Input Collector on both the canvas and table views. To reorder nodes on the canvas, select a given node inside the Input Collector and drag it up or down in the list. You can add or remove nodes
from an Input Collector, or nodes between multiple Input Collectors, by selecting a node and dragging it into or out of an Input Collector node on the canvas. To reorder nodes in an Input Collector in the table view, select a given
node in the list, then select the up or down arrow next to the node.

You can also set the number of times the Input Collector prompts a user for information before triggering a search instead. You can set the limit under
sn_vad_genai.input_collector_reprompt_limit in the System Properties \[sys_properties\] table. The minimum limit is 1, and the default limit is 2. With values greater than 2, the Input Collector reprompts the
user up to the set limit before starting a search. If you use very high values (such as 1000), you effectively disable automatic searches, and continue collecting information through additional reprompts.

Specify the flow action properties for the
node that you want to create.  
{#va-ai-data-collector__ai-data-collector-properties-sheet-table__entry__2}

| Property | Description |
|-|-|
| Node name | Name that identifies this node in the topic flow. |
| Advanced ||
| Additional instructions for LLM | Further instructions to the LLM, such as adding data formats, restrictions, or default values for user responses. You can create additional instructions in plain language, input a script, or define conditions with the data pill picker. |
| Confirmation message | Toggle switch to display a summary of collected inputs to the user at the end of a conversation. If Summary message is activated, the Virtual Agent (when activated) presents the information that you have entered and asks if everything is correct. Select Yes to continue the chat or No to restart collecting user input. You can also reply by typing a response in the chat window, to confirm or deny the summary or to change your answer. This option is active by default, and shows an enabled icon ![]() when activated. |
| Hide or skip this node ||
| Conditionally show this node if | No-code condition statement or low-code script that specifies a condition for presenting this node in the conversation. The condition must evaluate to true. |
| Allow user to skip this node if | No-code condition statement or low-code script that specifies a condition for letting users skip this node in the conversation. The condition must evaluate to true. You can set this field using either the condition builder or a script. |
[ ]

{#va-ai-data-collector__ai-data-collector-properties-sheet-table}

## Example Input Collector capability {#va-ai-data-collector__section_s5f_csj_dxb}

## Input Collector canvas view {#va-ai-data-collector__section_qkt_cw5_s1c}

## Input Collector table view {#va-ai-data-collector__id_zcl_xv5_s1c}

## Channel support {#va-ai-data-collector__id_myw_5lc_tzb}

{#va-ai-data-collector__table_lzq_fwb_rsb_xyzz__entry__3}

| Channel | Support | Constraints |
|-|-|-|
| Microsoft Teams | Supported | None |
| Slack | Not supported | Not applicable |
| SMS Twilio | Supported | Not applicable |
| WhatsApp | Not supported | Not applicable |
| Google Chat | Supported | None |
[Table 1. Channel support for the Input Collector control]

{#va-ai-data-collector__table_lzq_fwb_rsb_xyzz}