For this subtype of the Agentforce usage type, usage is calculated based on conversation windows. A conversation window starts when one of the following happens:
- when the user sends a message for the first time after the previous conversation window ends
- when ASA sends a pre-configured welcome message first
The end of the conversation window differs for each Digital Engagement channel on which ASA is enabled.
For the Messaging for In-App and Web channels:
- Messaging for Web: For unauthenticated users, the conversation window ends when the user explicitly clicks End Conversation. For authenticated users, the conversation window ends 24 hours after the start of the conversation.
- Messaging for In-App: The conversation window ends 24 hours after the start of the conversation.
For these channels, the conversation window ends 24 hours after the start of the conversation:
- Enhanced WhatsApp
- Enhanced Facebook Messenger
- Enhanced Apple Messages for Business
- Enhanced SMS
- Bring Your Own Channel
- Enhanced LINE
Agentforce Guided Shopping Agent (ASA) supports only inbound conversations, which are conversations that a user initiates. See Generative AI Billable Usage Types.
Einstein Requests is a usage metric for generative AI. The use of generative AI capabilities, in either a production or a sandbox environment, consumes Einstein Requests and possibly Data 360 credits. To learn more, see Data 360 Billable Usage Types.
API calls to the LLM gateway use Einstein Requests. For each API call to the LLM gateway, the number of Einstein requests used depends on the API call size factor and the LLM usage type multiplier. To learn more, see the Rate Card for Einstein Requests.
Einstein Requests are available in:
- Enterprise, Performance, and Unlimited editions with an Einstein for Sales, Einstein for Platform, or Einstein for Service add-on. To purchase the Einstein for Sales, Einstein for Platform, or Einstein for Service add-on, contact your Salesforce account executive.
- All Einstein 1 Editions
- Marketing Cloud - Growth - Enterprise Edition and Marketing Cloud - Growth - Unlimited Edition
Usage is calculated based on the number of records processed.
The count of records processed depends on the structure of a query as well as other related factors, such as the total number of records in the objects being queried.
Usage is calculated based on the amount of unstructured data that is processed. For example, if the search index processes 100 PDF documents that are 1 MB each, usage is calculated as 100 MB. If the search index processes five audio/video files that are on average 100MB each, usage is calculated as 500MB.
In Data 360, unstructured data is sometimes chunked and vectorized using an embedding model. Usage is computed only once across both these activities. For example, if one 100 MB PDF document is chunked and vectorized, usage is computed as 100 MB, not as 200MB.
Usage is determined by the number of standard agent actions. Each standard agent action includes the processing of up to 10,000 tokens. Tokens are units of data processed by AI models. Actions exceeding this limit are counted as a separate standard action each time the 10,000 token limit is exceeded. For example, processing 20,001 tokens is 3 standard actions. Actions involving lengthy prompts sent to the LLM can be counted as multiple actions where the 10,000 tokens per action limit is exceeded.
Standard agent actions are actions that are available out-of-the-box. To check the list of Standard actions, see Standard Action Reference.
Usage is determined by the number of custom actions. Each custom action includes the processing of up to 10,000 tokens. Tokens are units of data processed by AI models. Actions exceeding this limit are counted as a new custom action each time the 10,000 token limit is exceeded. For example, processing 20,001 tokens is 3 custom actions. Actions involving lengthy prompts sent to the LLM can be counted as multiple actions where the 10,000 token action per limit is exceeded.
Custom actions are actions that are created by you or which result from your modification of a standard action. To learn more about what customer created actions are, see Create a Custom Agent Action. To learn more about how standard actions become custom actions, see Editing Standard Agent Action Reference Actions.