---
sourceDocument: Australia ServiceNow AI Platform Capabilities
sourceDocumentLink: https://www.servicenow.com/docs/r/australia/servicenow-platform

 Release :

    - australia

ft:locale :

    - en-US

ft:publication_title :

    - Australia ServiceNow AI Platform Capabilities

ft:clusterId :

    - platcap

bundleId :

    - platcap

workflow :

    - Platform


---

# Software data gap remediation

# Software data gap remediation using the ingestion optimizer agentic workflow {#ariaid-title1}

Release version: Australia  
Updated September 30, 2026  
![](https://www.servicenow.com/docs/portal-asset/ico-clock) 3 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 Software data gap remediation using the ingestion optimizer agentic workflow

The CMDB ingestion optimizer agentic workflow in ServiceNow Australia release helps identify and remediate software data and attribute gaps within the Configuration Management Database (CMDB).
These gaps occur when software products or Configuration Item (CI) classes lack coverage from existing ingestion sources, resulting in missing key data such as version, edition, or CPU information.
Addressing these gaps is essential for improving Software Asset Management (SAM) license calculation accuracy and enhancing overall CMDB data quality.
Show full answer Show less  

## Causes of Software Data and Attribute Gaps

* **No Discovery pattern:** Missing Discovery patterns to identify software versions or editions.
* **No Service Graph Connector mapping:** Absence of connectors that map required CI attributes like CPU count.
* **No specialized ingestion tool:** Lack of purpose-built tools for specific publishers or platforms (e.g., database collectors, endpoint management tools).
* **Unsupported infrastructure types:** Environments using containerized, multi-cloud, or event-driven workloads that standard Discovery does not cover.

## Remediation Actions and Recommendations

The workflow provides targeted recommendations to close data gaps by suggesting ingestion sources categorized into three groups:

* **Discovery pattern recommendations:** Ranked by attribute coverage for affected software products.
* **Service Graph Connector recommendations:** Ranked connectors that map required CI class attributes.
* **Specialized ingestion tools:** Tools tailored for specific platforms, such as Oracle GLAS for Oracle databases and Java workloads.
* **Agent Client Collector (ACC):** For infrastructure components not covered by standard Discovery.
* **Client management tools:** Endpoint management solutions like SCCM, Intune, Tanium, and JAMF for software typically inventoried outside Discovery.

Recommendations appear by category---Software products, CI classes, and Infrastructure---and are only shown when applicable ingestion sources exist for the gap.

## AI-Triggered Remediation and User Interaction

The Software Asset Management advisor dashboard includes CMDB data quality insights featuring cards such as "Software installs missing version" and "CIs missing CPU attributes." Each card offers an **Ask Otto** action, which opens a conversational panel with the CMDB ingestion optimizer agent. This agent summarizes affected items and provides ranked ingestion source recommendations to close data gaps.

Access to Ask Otto requires the `nowassistpaneluser` role, and the dashboard cards require `samadmin` or `sncmdbadmin` roles. The agentic workflow activates automatically without additional feature flags or activation steps.

## Supported Ingestion Sources

* Discovery patterns for software products and CI classes.
* Service Graph Connectors for CI classes with required attribute mappings.
* Specialized ingestion tools like Oracle GLAS.
* Agent Client Collector for infrastructure components beyond standard Discovery reach.
* Client management tools such as SCCM, Intune, Tanium, and JAMF.

By leveraging these ingestion sources through the workflow's recommendations, ServiceNow customers can systematically improve CMDB completeness and SAM effectiveness.  
The CMDB ingestion optimizer agentic workflow recommends Discovery patterns, Service Graph Connectors, and specialized ingestion tools to close software data and attribute gaps in the CMDB.

A software product or CI class has a data or attribute gap when no available ingestion source covers it. Missing version, edition, or CPU data reduces the accuracy of license calculations in Software Asset Management (SAM) and lowers the CMDB data quality score.

The Software Asset Management advisor dashboard surfaces these gaps on charts such as Software installs missing version and CIs missing CPU attributes. The CMDB data quality insights generated by AI section on the same dashboard recommends how to close the gap for the affected software
products or CI classes.

## Causes of software data and attribute gaps {#na-cmdb-awf-ingestion-optimizer-c__ingestion-optimizer-concept-causes}

Several conditions can create a coverage gap for a software product or CI class:

* No Discovery pattern: A software product has no Discovery pattern that identifies its version or edition.
* No Service Graph Connector mapping: A CI class has no Service Graph Connector that maps the required attribute, such as CPU count or core count.
* No specialized ingestion tool: The environment lacks a purpose-built tool for the affected publisher or platform, such as a database-specific collector or an endpoint management tool.
* Unsupported infrastructure type: Containerized, multi-cloud, or event-driven workloads fall outside standard Discovery and require a dedicated ingestion approach.
{#na-cmdb-awf-ingestion-optimizer-c__ul_ingestion_optimizer_causes}

## Remediation actions {#na-cmdb-awf-ingestion-optimizer-c__ingestion-optimizer-concept-remediation}

The CMDB ingestion optimizer agentic workflow recommends ingestion sources that close a data or attribute gap for a specific software product or CI class.

* Discovery pattern recommendations: Ranked Discovery patterns for the affected software product, scored by the required attribute coverage each pattern provides.
* Service Graph Connector recommendations: Service Graph Connectors that map the affected CI class, ranked by class and attribute coverage.
* Specialized ingestion tools: Purpose-built tools for specific publishers or platforms, such as Oracle GLAS for Oracle database and Java workloads.
* Agent Client Collector recommendations: The Agent Client Collector (ACC) for infrastructure components that standard Discovery doesn't reach.
* Client management tool recommendations: Endpoint management tools such as SCCM, Intune, Tanium, and JAMF for software products typically inventoried outside Discovery.

{#na-cmdb-awf-ingestion-optimizer-c__ul_ingestion_optimizer_remediation}

Recommendations are organized into three categories: Software products, CI classes, and Infrastructure. Each
category groups the ingestion sources for that layer.

Not every software product or CI class has a recommendation in every category. When no ingestion source closes a gap, the workflow doesn't display a recommendation for that
category.

## AI-triggered remediation {#na-cmdb-awf-ingestion-optimizer-c__ingestion-optimizer-concept-ai-remediation}

For background on the CMDB data quality insights generated by AI section, see [Monitoring CMDB data quality using dashboard metrics in CMDB success advisor for SAM](https://www.servicenow.com/docs/access?context=cmdb-sa-sam-dashboard&version=australia&pubname=australia-it-asset-management&ft:locale=en-US). For background on the
Remediation actions panel, see [Improving CMDB data quality for SAM](https://www.servicenow.com/docs/access?context=cmdb-sa-sam-remediation&version=australia&pubname=australia-it-asset-management&ft:locale=en-US).

The CMDB data quality insights generated by AI section on the Software Asset Management advisor dashboard includes the Software installs missing version and CIs missing CPU attributes cards. Both cards include an Ask Otto action.

Selecting Ask Otto opens a ServiceNow Otto panel conversation with the CMDB ingestion optimizer agent.

The conversation first displays a brief summary of the affected software products or CI classes while the agent analyzes ingestion sources. It then opens the full set of ranked
recommendations in an expanded panel.

The Ask Otto action requires the now_assist_panel_user role. Both cards also require the sam_admin role or the sn_cmdb_admin role. Unlike some other CMDB success advisor agents, the CMDB ingestion optimizer agent doesn't require a feature flag or a separate activation step.

If you hold only the CMDB success advisor scope-user role, the Ask Otto action on the card links to the affected installs instead of opening an agent conversation.  
Note:  
If the agent conversation fails to start, an error notification appears and the Ask Otto action remains available to try again.

## Supported ingestion sources {#na-cmdb-awf-ingestion-optimizer-c__ingestion-optimizer-concept-sources}

The CMDB ingestion optimizer agentic workflow supports the following ingestion source types:

* Discovery patterns for software products and CI classes with an existing Discovery pattern.
* Service Graph Connectors for CI classes with a connector that maps the required attribute.
* Specialized ingestion tools, such as Oracle GLAS for Oracle database and Java workloads.
* The Agent Client Collector for infrastructure components that standard Discovery doesn't reach.
* Client management tools, such as SCCM, Intune, Tanium, and JAMF.
{#na-cmdb-awf-ingestion-optimizer-c__ul_ingestion_optimizer_sources}