Supporting information for ServiceNow Otto for Customer Service Management (CSM)
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Summary of Supporting information for ServiceNow Otto for Customer Service Management (CSM)
ServiceNow Otto for Customer Service Management (CSM) is an AI-powered application designed to enhance customer service operations by leveraging large language models (LLMs) and Now Assist skills. It is supported from the Vancouver Patch 4 release onward and integrates AI capabilities such as chat summarization, case summarization, resolution notes generation, and sentiment analysis within CSM workflows.
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Supported Versions and AI Models
The application supports multiple AI model providers including Now LLM Service, Now LLM Long Term Stable models (LTS), Azure OpenAI, Google Gemini, and Anthropic Claude on AWS. Administrators can configure which AI options are available via AI Control Tower and set preferences at the skill level through the AI Admin Hub console.
Supported User Interfaces and Skills
ServiceNow Otto for CSM delivers AI skills across different interfaces:
- CSM Configurable Workspace: Skills include chat summarization, case summarization, resolution notes generation, knowledge article generation, call summarization, sidebar discussion, chat recommendation, email response, sentiment analysis, suggested steps generation, and dashboards for sentiment and trending topics.
- Core UI: Skills include case summarization, resolution notes generation, knowledge article generation, sentiment analysis, and activity response generation.
Language Support
The application supports multiple languages for all skills, including German, French, Japanese, Dutch, French Canadian, Spanish, Brazilian Portuguese, and Italian, enabling multilingual customer service interactions.
Role Masking for Security
Role masking enhances security by restricting user access to AI agentic workflows, standalone AI agents, and skills based on the user’s active role. This mechanism works alongside Access Control Lists (ACLs) to ensure users only access data and AI-generated outputs relevant to their permissions.
For example, when a skill like Case Summarization is used, the system first retrieves data filtered by ACLs for the user’s active role and then applies role masking to the LLM-generated summary. This two-step control prevents unauthorized exposure of sensitive information while delivering tailored insights.
Application Activation and Dependencies
To enable ServiceNow Otto for CSM, customers must activate the sncsmgenai store app, which depends on the Customer Service (com.sncustomerservice) and UXC Generative AI (snuxcgenai) applications. These should be activated in the following order for proper functionality:
- Customer Service
- UXC Generative AI
- ServiceNow Otto for CSM
This setup allows customers to utilize chat and case summarization skills and generate case resolution notes to improve agent productivity and customer experience.
Get a quick overview of the important information that is related to the ServiceNow Otto for Customer Service Management (CSM) application.
Supported versions
ServiceNow Otto for CSM is supported starting with Vancouver Patch 4.
Supported language models
You can use Now LLM Service, Now LLM Long Term Stable models (LTS), Azure OpenAI, Google Gemini or Anthropic Claude on AWS as the AI model provider for all Now Assist skills and AI agents. Use the Configuration Controls in AI Control Tower to define which options are available, then set the skill-level preferences in the AI Admin Hub console. For more information, see Large language models on the ServiceNow AI Platform®.
Supported user interfaces
| Interface | Skill |
|---|---|
| CSM Configurable Workspace |
|
| Core UI |
|
Languages supported
- German
- French
- Japanese
- Dutch
- French Canadian
- Spanish
- Brazilian Portuguese
- Italian
Role masking for ServiceNow Otto for CSM agentic workflows, AI agents, and skills
Role masking is used to restrict user access to agentic workflows, standalone AI agents, and skills. This ensures that users only receive the permissions necessary for their tasks, enhancing security and reducing the risk of unauthorized access.
Imagine a user assigned roles A, B, and C, where each role grants access to a specific set of data. Normally, only if using Access Control Lists (ACLs), the user could access any data or functions available to roles A, B, and C. With role masking applied, the user can only access data tied to the active role, limiting exposure to unnecessary information.
When a CSM skill runs, its features are initially controlled by ACL permissions, ensuring users only access authorized data and functions. If the skill uses a Large Language Model (LLM) to perform its task, role masking adds an extra layer of control by filtering the LLM-generated output according to the user’s active role.
- Data Retrieval
ACL permissions for role A are applied to fetch relevant case data. This ensures the user only sees data they are authorized to view.
- Data Summarization
After data retrieval, an LLM summarizes the case. Role masking is then applied to the output, tailoring the summary to the access privileges defined for role A.
By applying both ACL permissions and role masking, the system ensures a secure and granular access control mechanism for CSM skills, protecting sensitive information while providing users with the insights they need to perform their tasks effectively. For information on role masking, see.
Application information
Activate the ServiceNow Otto for CSM store app (sn_csm_gen_ai) to use the chat and case summarization skills and to generate case resolution notes.
- Customer Service (com.sn_customerservice)
- UXC Generative AI (sn_uxc_gen_ai)
- Customer Service
- UXC Generative AI
- ServiceNow Otto for CSM
For more information, see Configuring ServiceNow Otto for Customer Service Management (CSM).