**Source URL:** https://commercial.veevavault.help/en/lr/1119332/index.md # Configuring Custom Vault AI Metadata
Vault AI metadata allows you to provide an additional layer of detail on your Vault data model to agents. With Vault AI metadata, you can define details related to the purpose of specific entities, such as objects, documents, and fields, which can include the business context, synonyms, and thorough descriptions. For example, a user may include a _Security Tree_-class object in a Vault AI Chat query. The agent may not understand the purpose of the object, when and when not to use it, and how to use it in the query. In this case, Vault AI metadata can help agents accurately interpret the object when it is included in a query and generate an appropriate response. You can define Vault AI metadata for entities and Picklists. Each entity (objects and document types) can also include metadata for fields, object relationships, and metrics. Each Picklist can include metadata for a Picklist, object lifecycle values, and Picklist values. When these components are included in agent context, instructions, or tool configurations, the agent uses the metadata to execute queries properly. Without metadata, agents typically can only query _Name_ and _Label_ field values, which can lead to misunderstandings and inaccurate responses. Vault AI metadata ensures agents can see the whole picture of your Vault data model and not just surface level details. Agent permission to entities and Picklists with metadata is determined by the assigned agent user's permissions.
## Synonyms You can assign synonyms to Vault AI metadata, which allows agents to query different terms and phrases related to the entities, fields, relationships, Picklists, and metrics. Synonyms do not allow for exact matches, meaning agents must still interpret the synonym to determine which data it refers to. For example, synonyms for a _Region_ field could include _District_, _Territory_, and _Zone_. When a user enters one of the synonyms in Vault AI Chat, the agent knows it is related to the _Region_ field and continues to generate an appropriate response. Agents can also verify typos and route to the appropriate data, such as _Regoin_ for _Region_. When writing a synonym, avoid obvious phrases, such as _marketing brochures_, _marketing brochure record_, and _marketing brochure item_ for a _Marketing Brochure_ object. Instead, use jargon, abbreviations, or terms an agent cannot use to map to data in your Vault. For example, you could use synonyms such as _collateral_, _leave-behinds_, _leaflets_, and _GTM_ for a _Marketing Brochure_ object. ## How to Configure Entity Metadata To define an entity's metadata: 1. Navigate to **Admin** > **Configuration** > **Vault AI Metadata** > **Entities**. 2. Click **Create**. 3. Select **Object** or **Doctype** from the **Type** drop-down. 4. Based on your **Type** selection, select an active object or document type from the **Target** drop-down. You cannot change this selection after saving the entity. You can only select objects and document types not already in use by another entity. 5. The **Target Label** and **Label** are populated based on your **Target** selection. Update the **Label** value as needed. The **Target Label** value is updated if the selected object or document type's _Label_ is updated. 6. Enter an API **Name**. 7. Enter a **Description**. The _Description_ should include details on how an agent should interpret the entity. For example, you can include when the agent can and cannot use the entity, how the agent should use the entity, and its overall purpose. Ensure the description is clear and concise. A clear and accurate description ensures agents can properly interpret the entity. If there is already a description in place, you can override it by entering a new one. 8. Optional: Enter up to ten **Synonyms** for the entity. Type out the synonym and press **Enter** to add it. 9. Click **Save**. The entity is now configured with metadata. You can begin configuring metadata for fields, object relationships, and metrics related to the entity. ### How to Configure Field Metadata To configure an entity field's metadata: 1. Select **Fields** from the entity configuration page. This drop-down is only available after you've created and saved the entity metadata. 2. Click **Create**. 2. Select an active field from the entity in the **Target** drop-down. 4. The **Target Label** and **Label** are populated based on the **Target** selection. Update the **Label** as needed. The **Target Label** value is updated if the selected field's _Label_ is updated. 5. Enter an API **Name** for the field. 6. Enter a **Description**. The _Description_ should include details on how an agent should interpret the field. For example, you can include when the agent can and cannot use the field, how the agent should use the field, and its overall purpose. Ensure the description is clear and concise. A clear and accurate description ensures agents can properly interpret the field. If there is already a description in place, you can override it by entering a new one. 7. Optional: Enter up to ten **Synonyms**. Type out the synonym and press **Enter** to add it. 8. Optional: Enter up to ten **Example Values**. You can enter any term or phrase a user may enter in the selected _Target_ field. The _Example Values_ field is available only if the **Target** is a Text field. 9. Optional: If the _Target_ field is a Picklist with metadata configured, you can override the metadata settings for it or any of its values. Enter a new **Picklist Description** and **Picklist Synonyms** as needed. The Picklist's defined metadata settings are used instead if you do not override them. 10. Click **Save**. The entity field's metadata is now configured. When an agent queries this field, it uses this metadata to generate an appropriate response. ### How to Configure Object Relationship Metadata Relationship configuration is only available for object entities. To configure object relationship metadata: 1. Select **Relationships** from the entity configuration page. This drop-down is only available after you've created and saved the entity metadata. 2. Click **Create**. 3. Select an active object reference field on the entity's object from the **Target** drop-down. 4. The **Target Label** and **Label** are populated based on the **Target** selection. Update the **Label** as needed. The **Target Label** value is updated if the selected object reference field's _Label_ is updated. 5. Enter a **Description**. The _Description_ should include details on how an agent should interpret the object relationship. For example, you can include when the agent can and cannot use the object relationship, how the agent should use it, and its overall purpose. Ensure the description is clear and concise. A clear and accurate description ensures agents can properly interpret the object relationship. If there is already a description in place, you can override it by entering a new one. 6. Enter up to ten **Synonyms**. Type out the synonym and press **Enter** to add it. 7. Click **Save**. The object relationship metadata is now configured. When an agent queries this relationship, it uses this metadata to generate an appropriate response. The _Cardinality_ field displays the type of relationship: [_ONE-TO-ONE_](/en/lr/28740/#parent-child-relationships), [_MANY-TO-ONE_](/en/lr/28740/#many_to_many), [_ONE-TO-MANY_](/en/lr/28740/#parent-child-relationships), [_MANY-TO-MANY_](/en/lr/28740/#many_to_many). If the _Cardinality_ is _MANY-TO-MANY_, the _Name_ of the join object used in that relationship is populated in the _Join Object_ field.
### How to Configure Metrics Metadata Vault AI metadata for metrics specifies which fields to use and how to calculate them when a user asks a metric related question in Vault AI Chat. For example, a user may ask how many days a document review is overdue or how much time they have until a review period closes. In such scenarios, if the agent cannot map the data to a single field, it attempts to map and combine data across multiple fields using existing field _Label_ values, which could lead to inaccurate results. To configure metadata for an entity's metrics: 1. Select **Metrics** from the entity configuration page. This drop-down is only available after you've created and saved the entity metadata. 2. Click **Create**. 3. Enter a **Label**. 4. Enter an API **Name**. 5. Enter a **Description**. The _Description_ should include details on exactly what the metric represents. For example, you can include when the agent can and cannot use the metric, how the agent should use the metric, and the metric's overall purpose. Ensure the description is clear and concise. A clear and accurate description ensures agents can properly interpret the metric. If there is already a description in place, you can override it by entering a new one. 6. Enter up to ten **Synonyms**. Type out the synonym and press **Enter** to add it. 7. Select up to ten **Target Fields**. Agents can use these fields when querying the metrics of your metadata. 8. Enter **Instructions** using a Vault formula or rule. Do not restate the _Description_ here. The _Instructions_ should tell the agent how to calculate the metric, which fields to use and combine, and any applicable conditions. 9. Click **Save**. The metric metadata is now saved. When an agent queries the metric, it uses this Vault AI metadata to generate a response. ## How to Configure Picklist Metadata To configure a Picklist's metadata: 1. Navigate to **Admin** > **Configuration** > **Vault AI Metadata** > **Picklists**. 2. Click **Create**. 3. Select **Picklist** or **Objectlifecycle** from the **Type** drop-down. 4. Based on your **Type** selection, select a Picklist or object lifecycle from the **Target** drop-down. 5. The **Target Label** and **Label** are populated based on the **Target** selection. Update the **Label** as needed. The **Target Label** value is updated if the selected Picklist's or object lifecycle's _Label_ is updated. 6. Enter a **Description**. The _Description_ should include details on how an agent should interpret the Picklist. For example, you can include when the agent can and cannot use the Picklist, how the agent should use the Picklist, and its overall purpose. Ensure the description is clear and concise. A clear and accurate description ensures agents can properly interpret the Picklist. If there is already a description in place, you can override it by entering a new one. 7. Enter up to ten **Synonyms**. Type out the synonym and press **Enter** to add it. 8. Click **Save**. The Picklist metadata is now configured. You can begin configuring metadata for each value in the Picklist or state in the object lifecycle.
### How to Configure Picklist Value & Lifecycle State Metadata To configure metadata for a Picklist value or an object lifecycle state: 1. Select **Picklist Values** on the Picklist configuration page. This drop-down is only available after you've created and saved the Picklist metadata. 2. Click **Create**. 3. Select a **Target**. If the parent entity is a Picklist, select a value from the Picklist. If the parent entity is an object lifecycle, select a state. 4. The **Target Label** and **Label** are populated based on the **Target** selection. Update the **Label** as needed. The **Target Label** value is updated if the selected value's or state's _Label_ is updated. 5. Enter an API **Name**. 6. Set the **Status** if necessary. **Active** is selected by default. 7. Enter a **Description**. The _Description_ should include details on how an agent should interpret the Picklist value or object lifecycle state. For example, you can include when the agent can and cannot use the values, how the agent should use the values and their overall purpose. Ensure the description is clear and concise. A clear and accurate description ensures agents can properly interpret the value. If there is already a description in place, you can override it by entering a new one. 8. Optional: Enter up to ten **Synonyms**. Type out the synonym and press **Enter** to add it. 9. Click **Save**. The Picklist value or object lifecycle state metadata is now configured. When an agent queries a value or state, the metadata is used to generate an accurate response. ## Deleting a Metadata Entity or Picklist If an entity is referenced in an agent context, Vault displays a warning before it is deleted. If deleted, the agent context can no longer use the entity. If an entity is deleted, all of its related field, object relationship, and metric metadata are deleted as well. The same behavior applies to Picklists and any related Picklist values. If a _Target_ referenced by an entity, field, object relationship, metric, Picklist, or Picklist value is deleted, its associated metadata is also deleted. ## Best Practices The following best practices apply to creating Vault AI metadata: * It is recommended to create Vault AI metadata for the following types of objects and document types: * High-traffic objects and document types that appear often in Vault AI Chat inquiries * Objects and document types with names that do not clearly convey their purpose * Objects and document types with similar related objects or document types, such as any object that an agent could confuse with another * Picklists on key filter fields, if a Picklist determines how users phrase queries, define Picklist and Picklist value metadata * Only add metric metadata when a query requires combining data across multiple fields, such as calculating a duration between two dates, or aggregating data across multiple objects, such as _Categories_, _Sites_, and _Studies_. * Use _Example Values_ when a Text field may contain common terms or phrases users reference in Vault AI Chat queries. If there are not predictable terms or phrases a user may enter in the field, leave _Example Values_ blank. * Add object relationship metadata if the relationship _Name_ does not clearly convey its purpose, the context is not clear, or you want to specifically guide the agent on how to use and not use the relationship in queries. ## Limits The following limits apply to creating Vault AI metadata for _Entities_ and _Picklists_: * Up to 50 custom _Entities_ per Vault * Up to 50 fields per entity * Up to 30 object relationships per entity * Up to 20 metrics per entity * Up to 45 _Target Fields_ per metric * Up to 100 Picklist per Vault * Up to 50 values per Picklist * Up to 10 values per synonym * Up to 10 example values per field * Multiple _Entities_ cannot reference the same object, document type, field, object relationship, or metric. ## Related Permissions | Type | Permission Label | Controls | | --- | --- | --- | | Security Profile | Admin: Configuration: AI Metadata: Read | Controls your ability to view Vault AI metadata | | Security Profile | Admin: Configuration: AI Metadata: Create | Controls your ability to create Vault AI metadata | | Security Profile | Admin: Configuration: AI Metadata: Edit | Controls your ability to edit Vault AI metadata | | Security Profile | Admin: Configuration: AI Metadata: Delete | Controls your ability to delete Vault AI metadata |