Using Enterprise graph schema
Summarize
Summary of Using Enterprise Graph Schema
The Enterprise Graph schema enables accurate natural language query responses across your entire ServiceNow database. This pre-configured Knowledge Graph schema maps instance tables and their connections, facilitating comprehensive data retrieval without the need for custom schema creation.
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Key Features
- Natural Language Queries: Supports queries across all tables, enhancing data accessibility.
- Integration with AI Agents: Admins can select Enterprise Graph for AI agents, NA Virtual Agent, or NA Panel admin, improving query response accuracy with tagging.
- Modes of Operation:
- Regular Mode: Ideal for environments with over 50 tables, prioritizing tagged tables for searches.
- Enterprise Graph (Small): Focuses on specific tagged tables, beneficial for latency-sensitive scenarios.
- Tagging Requirement: Tags must be assigned to key tables for effective natural language responses in both modes.
Key Outcomes
Utilizing the Enterprise Graph schema allows:
- Enhanced response capabilities for Now Assist Virtual Agents, deflecting a wider array of queries.
- Increased productivity for fulfillers via the Now Assist Panel, enabling insights from structured data through natural language questions.
- AI agents to retrieve relevant information directly from the Knowledge Graph, providing essential context for task completion.
Use Enterprise Graph for accurate natural language query responses, across the entire database.
Enterprise graph is a pre-configured Knowledge Graph schema that maps all instance tables and their connections, enabling natural language queries for data across all tables.
To see some examples of the Natural Language query responses, refer Natural language queries use cases and examples.
Enterprise graph schema simplifies Knowledge Graph setup by providing a preconfigured schema, eliminating the need for custom schema creation in Knowledge Graph designer.
Admins can choose Enterprise graph as the Knowledge Graph schema when using AI agents, NA Virtual Agent, or NA Panel admin and add tags to enhance accuracy.
By mapping all tables, the Enterprise graph schema expands query capabilities to cover the entire database, whereas a custom or out-of-the-box (OOTB) schema limits queries to only the tables included in its specific schema.
Benefits of Enterprise Graph on Prebuilt integration
Now Assist Virtual Agent- With Enterprise Graph integration, Now Assist Virtual Agents can respond to a wide range of questions about their enterprise data from requester, helping to deflect queries.
Now Assist Panel- With Enterprise Graph enabled, Now Assist Panel allows fulfillers to obtain insights from the structured data in instance by asking natural language questions, which boosts their productivity.
AI agents- With Enterprise Graph enabled, AI agents can access relevant information from structured data in ServiceNow instance directly from the Knowledge Graph, giving them essential context for tasks.
Modes of Enterprise Graph
- Enterprise Graph- regular mode
- Enterprise Graph (Small)
Regular mode is used for use cases with large number of tables (more than 50 tables), to:
- Searches across all tables, but gives more priority to tables which are included in the tag added at time of configuring Enterprise Graph in the consuming app (AI agent or VA).
- Useful for scenarios where answer is expected from large number of tables.
- Searches only within tables which are included in the tag added at time of configuring Enterprise Graph (Small) in consuming app (AI agent or VA). Tagging is mandatory in this mode.
- Useful for latency-sensitive use cases with limit of 50 tables
Tags in Knowledge Graph
Tags are lists of key tables that are important for answering natural language questions in a specific use case. They are required to be used with Enterprise Graph and Enterprise Graph (Small).