Software data gap remediation using the ingestion optimizer agentic workflow
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
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.
Remediation actions
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.
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
For background on the CMDB data quality insights generated by AI section, see . For background on the Remediation actions panel, see .
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
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.
--- title: Software data gap remediation using the ingestion optimizer agentic workflow description: 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. locale: en-US canonical_url: https://www.servicenow.com/docs/r/australia/servicenow-platform/now-assist-for-configuration-management-database-cmdb/na-cmdb-awf-ingestion-optimizer-c.html release: australia product: Now Assist for Configuration Management Database \(CMDB\) classification: now-assist-for-configuration-management-database-cmdb topic_type: concept last_updated: "2026-09-30" reading_time_minutes: 3 keywords: [CMDB ingestion optimizer, ingestion source recommendations, software data gaps, CI attribute gaps] breadcrumb: [Use generative AI skills, ServiceNow Otto for Configuration Management Database \(CMDB\), Configuration Management Database \(CMDB\), Configuration Management, Extend ServiceNow AI Platform capabilities] --- # Software data gap remediation using the ingestion optimizer agentic workflow 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 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. ## Remediation actions 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. 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 For background on the **CMDB data quality insights generated by AI** section, see . For background on the Remediation actions panel, see . 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 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.
| title | Software data gap remediation using the ingestion optimizer agentic workflow |
| description | 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. |
| locale | en-US |
| canonical_url | https://www.servicenow.com/docs/r/australia/servicenow-platform/now-assist-for-configuration-management-database-cmdb/na-cmdb-awf-ingestion-optimizer-c.html |
| release | australia |
| product | Now Assist for Configuration Management Database \(CMDB\) |
| classification | now-assist-for-configuration-management-database-cmdb |
| topic_type | concept |
| last_updated | 2026-09-30 |
| reading_time_minutes | 3 |
| keywords | CMDB ingestion optimizeringestion source recommendationssoftware data gapsCI attribute gaps |
| breadcrumb | Use generative AI skillsServiceNow Otto for Configuration Management Database \(CMDB\)Configuration Management Database \(CMDB\)Configuration ManagementExtend ServiceNow AI Platform capabilities |