Considerations for Agentforce Employee Agent

Before setting up an Agentforce Employee agent, keep these considerations in mind.

Required Editions

Available in: Lightning Experience
Available in: Enterprise, Performance, Unlimited, and Developer Editions. Required add-on licenses vary by agent type.

Employee Agent Language and Locale Support

Agentforce Employee agent supports these languages and locales.

Note
Note

This list is for languages supported by Agentforce. For a list of languages supported by the Salesforce platform as a whole, see Supported Languages.

Language Code
English en_AU
en_GB
en_US
Afrikaans (Beta) af
Arabic (Beta) ar
Armenian (Beta) hy
Bengali (Beta) bn
Bosnian (Beta) bs
Bulgarian bg
Catalan ca
Chinese Simplified zh_CN
Chinese Traditional zh_TW
Croatian hr
Czech cs
Dutch nl-NL
nl-BE
Danish da
Estonian et
Farsi (Beta) fa
Finnish fi
French fr_CA
fr_FR
German de
Greek el
Gujarati (Beta) gu
Hebrew (Beta) he
Hindi hi
Hungarian hu
Icelandic (Beta) is
Indonesian id
Italian it
Japanese ja
Kannada (Beta) kn
Kazakh (Beta) kk
Korean ko
Latvian (Beta) lv
Lithuanian (Beta) lt
Macedonian (Beta) mk
Malay ms
Malayalam (Beta) ml
Marathi (Beta) mr
Norwegian no
Polish pl
Portuguese pt_BR
pt_PT
Punjabi (Beta) pa
Romanian ro
Russian (Beta) ru
Serbian (Beta) sr
Slovak (Beta) sk
Spanish es_ES
es_MX
Swedish sv
Tagalog tl
Tamil (Beta) ta
Te reo (Beta) mi
Telugu (Beta) te
Thai th
Turkish tr
Ukrainian (Beta) uk
Urdu (Beta) ur
Vietnamese vi

See Agentforce Considerations for additional language and locale support considerations.

Employee Agent Large Language Model Support

The Agentforce platform supports OpenAI GPT-4o for reasoning engine calls. Agent actions can make calls to other predefined LLMs. Bringing your own model isn’t supported, but custom actions that execute prompt templates can use any Salesforce-managed model. See Large Language Model Support.

Model
OpenAI GPT-4o

Einstein Trust Layer Service Support

Agentforce Employee agent supports these Trust Layer services.

Einstein Trust Layer service Description
Zero Data Retention Policy Einstein Trust Layer uses a zero-data retention policy, so no data is stored or used for model training by third-party LLMs. Customers’ use of other features including agents may result in data storage. For more information, contact your Salesforce account executive.
Dynamic Grounding with Secure Data Retrieval Relevant information from trusted company data, your knowledge base, or other sources you configure, is used to answer a question.
Prompt Defense (System policies and prompt injection detection) System policies help limit hallucinations and decrease the likelihood of unintended or harmful outputs by the LLM.
Toxicity Detection Potentially harmful LLM responses are detected and flagged.
Audit and Feedback Prompts, responses, and trust signals are logged and stored in Data 360, giving you visibility into the results of each user interaction. Feedback can be used to improve instructions, prompt templates, and more.

Data masking through the Einstein Trust Layer is disabled to improve the performance and accuracy of agents. Ask your system administrator about which Einstein Trust Layer services are enabled in your org and available for employee agents.

Usage Types Billed by Agentforce Employee Agent

Agentforce Employee agents use generative AI in prompt executions and use Data 360 to ingest, store, and process data. Use of Agentforce Employee agents impacts the consumption of billing credits in these usage types. Before deployment, work with your Salesforce account team to confirm license availability and plan credit usage.

Tip
Tip This feature has access to Digital Wallet, a free account management tool that offers near real-time consumption data for enabled products across your active contracts. Access Digital Wallet and start tracking your org's usage. To learn more, see About Digital Wallet.

Metered and Unmetered Consumption

Agentforce Employee agent usage is either metered or unmetered, depending on the permissions assigned to the interacting user. Unmetered usage applies if a user has the Unmetered User-Based AI permission. For more information, see Considerations for Unmetered Agentforce Usage.

Usage Types for Metered Usage

Digital Wallet Card Usage Type Description Notes
Flex Credits Standard Action

Usage is determined by the number of standard actions called by the agent in a text conversation. Currently, every standard action called by the agent is metered as one standard action, irrespective of the number of tokens processed.

Standard agent actions are actions that are available out-of-the-box. To check the list of Standard actions, see Standard Action Reference.

Note
Note Use of some standard agent actions require that a subscription has been purchased for each user that accesses these actions, such as a subscription to Agentforce for Sales Add-on or Agentforce for Service Add-on. To determine which subscription is required for such standard actions, see Standard Action Reference at Standard Action Reference. While this requirement is not technically enforced yet, users who don’t have the required add-on license will lose access to such actions for which they don’t have a license when the requirement is enforced.
This usage type isn’t billed when it's associated with a generative AI action that qualifies as unmetered human context usage. For more information, see Generative AI Usage and Billing.
Flex Credits Custom Action

Usage is determined by the number of custom actions called by the agent in a text conversation. Currently, every custom action called by the agent is metered as one custom action, irrespective of the number of tokens processed.

Async calls to Salesforce AI in custom action implementation may incur additional charges.

This usage type isn’t billed when it's associated with a generative AI action that qualifies as unmetered human context usage. For more information, see Generative AI Usage and Billing.

When you use Agentforce Employee agents, credits can be consumed in usage types on other consumption cards by related features such as Agentforce Data Library or Audit and Feedback.

Other Considerations

Agentforce Employee agents are supported in employee channels, including the Agentforce panel in Lightning Experience, Slack, and the Salesforce mobile app.

  • If you plan to deploy multiple employee agents, describe each agent’s purpose, such as departmental scope or business function, to prevent overlapping subagents.
  • Grant access to specific Employee agents using permission sets or profiles based on employee roles or groups.
  • Connecting Employee agents to Slack or mobile apps involves additional authentication or licensing steps.
  • Maintain a clear and organized conversation design and subagent structure to drive consistent performance and usability as you scale your deployment.