--- sourceDocument: Brazil ServiceNow AI Platform Administration sourceDocumentLink: https://www.servicenow.com/docs/r/platform-administration Release : - brazil ft:locale : - en-US ft:publication_title : - Brazil ServiceNow AI Platform Administration ft:clusterId : - platadm bundleId : - platadm workflow : - Platform --- # Semantic Index Configuration form # Semantic Index Configuration form {#ariaid-title1} Release version: Brazil Updated September 10, 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 Semantic Index Configuration form The Semantic Index Configuration form in ServiceNow allows you to define and manage semantic indexing settings for AI Search indexed sources. This form is available only when the AI Search Semantic Controller plugin is active, which requires at least one ServiceNow Otto® application installed on your instance. It enables you to customize how semantic indexes are created and optimized for better AI-driven search experiences. Show full answer Show less ## Key Features * **Name:** Assign a unique, special-character-free name to your semantic index configuration to easily identify it (e.g., Knowledge-Table-semantic-index). * **Embedding Models:** Choose from multiple embedding models to generate semantic vectors: * ServiceNow Embedding (E5) -- default model with a 512-term encoder limit. * Azure OpenAI Embedding -- requires separate setup. * Google Gemini Embedding -- requires separate setup. * Custom Embedding -- allows use of custom fine-tuned models. * **Active:** Toggle to activate or deactivate the configuration. AI Search will ignore inactive configurations. * **Indexed Source:** Automatically set reference to the AI Search indexed source this configuration applies to. * **Application:** Automatically set application scope of the configuration record. * **Chunking Configuration:** Controls how text is chunked for embedding processing, optimizing semantic indexing: * **Chunking Strategy:** Choose between Passage (for longer text), Truncate, or Full Text (for shorter text). * **Overlap Sentences:** (Passage only) Number of sentences overlapped between chunks to improve recall at some cost to performance. * **Chunk Unit:** (Passage only) Decide whether chunks are measured in words or sentences. * **Chunk Size:** (Passage only) Maximum number of words or sentences per chunk. * **Maximum Total Words:** (Truncate only) Sets the max total words indexed when concatenating all fields. ## Key Outcomes * Allows precise customization of semantic indexing to improve AI Search relevance and performance based on your content and search needs. * Supports multiple embedding models, including third-party and custom embeddings, providing flexibility for advanced AI search use cases. * Enables control over text chunking strategies to balance indexing accuracy and performance for different types of content. * Ensures semantic index configurations are applied only when active, helping maintain efficient indexing and search operations. The Semantic Index Configuration form enables you to define semantic indexing settings for an AI Search indexed source. For details on defining and modifying semantic indexing settings for an indexed source, see [Configure semantic indexing settings for an indexed source](https://www.servicenow.com/docs/d_wOxuJAVE0zNW6TlKPNyQ "Specify the semantic indexing configuration settings you want to apply when AI Search indexes records from your indexed sources."). Note: This form is only available when the AI Search Semantic Controller plugin (com.glide.ais.semantic_search) is active on your instance. To activate this plugin, your instance must have at least one [ServiceNow Otto® application](https://www.servicenow.com/docs/access?context=platform-now-assist-landing&version=brazil&pubname=brazil-intelligent-experiences&ft:locale=en-US) installed. {#semantic-index-configuration-form__table_t1b_wjh_xcc__entry__2} | Field | Description | |-|-| | Name | Unique name for the semantic index generated by this semantic index configuration. As an example, if you're creating a semantic index configuration for the Knowledge Table indexed source, you might name it Knowledge-Table-semantic-index. Note: The semantic index's name can't contain special characters, underscores, or whitespace. | | Embedding Models | List of embedding models to use for the semantic index configuration. * Default value: ServiceNow Embedding (E5) * Supported values: * ServiceNow Embedding (E5): Use the E5 fine-tuned embedding model for content in the semantic index. The embedding model's encoder limit is 512 terms. * Azure OpenAI Embedding: Use the Azure OpenAI fine-tuned embedding model for content in the semantic index. For more information, see ../concept/setting-up-3p-embedding-models.html. * Google Gemini Embedding: Use the Google Gemini fine-tuned embedding model for content in the semantic index. For more information, see ../concept/setting-up-3p-embedding-models.html. * Custom Embedding: Use the custom fine-tuned embedding model for content in the semantic index. For more information, see ../concept/creating-byom.html. {#semantic-index-configuration-form__ul_o3v_r23_xcc} {#semantic-index-configuration-form__ul_wc2_flh_xcc} | | Active | Option to make the semantic index configuration active for your instance. AI Search ignores inactive semantic index configurations when indexing content from the specified index source. | | Indexed Source | Reference to the AI Search indexed source that you want to apply this semantic index configuration to. This field is automatically set. For more details on indexed sources, see [Indexed sources in AI Search](https://www.servicenow.com/docs/wbgc0tkdQcXHU63sXMrFeA "Indexed sources designate ServiceNow AI Platform tables and external document sets with alphanumeric text and string field content that you want to make searchable. AI Search ingests text and string fields from table records or external documents and stores their searchable alphanumeric content in its search index."). | | Application | Application scope for the semantic index configuration record. This field is automatically set. | | Chunking Configuration For Embedding || | Chunking Strategy | Strategy to use when chunking semantically indexed text for the embedding model. * Default value: Passage * Supported values: * Passage: Chunking strategy for longer text field values. Index text from semantic field values in chunks. Each chunk contains a maximum number of words or sentences determined by your Chunk Unit and Chunk Size selections. * Truncate: Chunking strategy for short text field values. Concatenate all semantic index field values, then perform semantic indexing for terms up to the Maximum Total Words limit. * Full Text: Chunking strategy for short text field values. Concatenate all semantic index fields, then perform semantic indexing for all terms up to the embedding model's encoder limit. {#semantic-index-configuration-form__ul_dkn_qlh_xcc} * Type: choice list {#semantic-index-configuration-form__ul_cfb_mlh_xcc} | | Overlap Sentences | Number of sentences to overlap between chunks when indexing text from semantic index field values. Higher overlap values increase recall for semantic vector search at the expense of performance. This field appears only when Passage is selected from Chunking Strategy. * Default value: 5 * Supported values: Any non-negative integer * Type: integer {#semantic-index-configuration-form__ul_scc_rg3_xcc} | | Chunk Unit | Textual unit to use as the basis for chunk size when indexing semantic field values for semantic vector search. This field appears only when Passage is selected from Chunking Strategy. * Default value: Words * Supported values: * Words: Use words as the textual unit by which semantic index field values are chunked. Each chunk can include up to Chunk Size words. * Sentences: Use sentences as the textual unit by which semantic index field values are chunked. Each chunk can include up to Chunk Size sentences. {#semantic-index-configuration-form__ul_www_cg3_xcc} * Type: choice list {#semantic-index-configuration-form__ul_qd3_cg3_xcc} | | Chunk Size | Maximum number of words or sentences (depending on your Chunk Unit selection) to include in a chunk when indexing semantic field values for semantic vector search. This field appears only when Passage is selected from Chunking Strategy. * Default value: 250 when Words is selected from Chunk Unit, or 15 when Sentences is selected from Chunk Unit * Supported values: Any non-negative integer * Type: integer {#semantic-index-configuration-form__ul_axg_jj3_xcc} | | Maximum Total Words | Maximum number of words to index for semantic vector search from the concatenated values of all semantic index fields. This field appears only when Truncate is selected from Chunking Strategy. * Default value: 500 * Supported values: Any non-negative integer * Type: integer {#semantic-index-configuration-form__ul_xzx_nj3_xcc} | [Table 1. Semantic Index Configuration form] {#semantic-index-configuration-form__table_t1b_wjh_xcc}