Multilingual service for Now Assist
Summarize
Summary of Multilingual service for Now Assist
The multilingual service for Now Assist applications allows communication in users' preferred languages by leveraging large language models (LLMs) for translation. The service determines the user's language preference based on their Language & Region settings or the text content itself. Currently, multiple LLM providers are supported, including Now LLM Service, Microsoft Azure OpenAI, Anthropic Claude, and Google Gemini, with Azure offering the most extensive language support.
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Key Features
- Native Translation: Allows direct communication in the user's language. If a user sends a message in a supported language, the LLM responds in that same language.
- Dynamic Translation: Translates non-English content to English before processing and then back to the user’s preferred language. This is used when a language is not natively supported.
- Language Support Groups: Languages are categorized into P1, P2, and P3 groups based on the level of native support and translation quality.
- Custom Language Addition: Users can add languages not included in the standard groups, provided they are supported by the LLM provider and properly configured.
Key Outcomes
By using the multilingual service, customers can enhance user experience by providing seamless communication in different languages, leading to improved engagement and satisfaction. Configuring the service to include additional languages allows for flexibility, ensuring that organizations can meet diverse user needs. Additionally, employing native translation prioritizes speed and accuracy, while Dynamic Translation ensures broader language coverage.
Now Assist applications use the multilingual capabilities of large language models (LLMs) to translate user-generated content.
Multilingual service overview
You can configure the multilingual services for Now Assist applications to communicate with your users in their preferred languages. The LLM detects the language used based on the user's language choice in their Language & Region preferences or the contents of the text, such as a conversation message.
Multilingual support is enabled for multiple LLM providers, such as Now LLM Service, Microsoft Azure OpenAI, Anthropic Claude on AWS, and Google Gemini. Azure OpenAI offers the most language support on the ServiceNow AI Platform.
How the different multilingual services work
The inherent multi-language capabilities of the LLM is called native translation. In native translation, text is sent as-is to the model and the model responds in the user's language. For example, if a user sends a message in Spanish, the multilingual LLM supports Spanish, so it receives the Spanish input directly from the user. It then generates a response in Spanish, regardless of the language used in the source material it uses to create that response.
For Dynamic Translation, once non-English content is detected, the translation service translates the content to English before sending the request to the large language model (LLM). After the LLM returns a response, the response is translated back into the user's preferred language for them to see. For example, a user enters a message in Slovenian. Dynamic Translation translates the Slovenian to English before giving the message to the LLM. The LLM generates a response in English, and then Dynamic Translation translates that response to Slovenian to show to the user.
If you enable both native translation and Dynamic Translation, native translation has preference and is used first.
Native translation
Supported languages are categorized into three basic groups.
P1 languages have the strongest native support across most model providers, meaning high-quality translation and generative capabilities with fewer errors. Nuance, idioms, and context are usually handled well because these languages are deeply integrated into the models.
P2 languages are supported natively by smaller ServiceNow models and most external providers, but not always by every model (e.g., some exceptions for Canadian French and Dutch). Accuracy is good, but there may be occasional gaps in nuanced understanding compared to P1 languages.
P3 languages include a broader set of languages supported by major providers like Microsoft Azure OpenAI, Google Gemini, and Anthropic Claude on AWS, but not natively by ServiceNow’s own large models. While coverage is comprehensive, these languages generally have less training depth, so subtle tone or idiomatic expressions may be harder to capture perfectly.
- P1
- English
- French
- German
- Italian
- Spanish
- Brazilian Portuguese
- P2
- Canadian French
- Japanese
- Dutch
- P3
- Swedish
- Finnish
- Czech
- Hebrew
- Hungarian
- Korean
- Norwegian
- Polish
- Portuguese
- Russian
- Simplified Chinese
- Traditional Chinese
- Thai
- Turkish
- Arabic
- Danish
Specific models vary in their support.
- ServiceNow Large Language Model v1 (Llama 3.3 70B) only supports English natively.
- ServiceNow Large Language Model v2 (GPT-OSS) supports English, French, German, Spanish, and Italian natively.
- ServiceNow Small Language Model v1 (Mistral Nemo 12B) and v2 (Apriel) supports all P1 and P2 languages.
- Microsoft Azure OpenAI GPT-4.1 and GPT-4.1-mini support more than 80 languages, including P1, P2, and P3.
- Google Gemini 2.5 Flash/2.5 Pro currently does not support French Canadian natively.
- Anthropic Claude 4.0 Sonnet currently does not support French Canadian or Dutch natively.
Adding languages beyond the P1, P2, or P3 language groups
Some providers, such as Azure OpenAI, offer additional language support beyond the P1, P2, and P3 language groups previously described. You can configure your instance to include additional languages.
- Ensure the language is on the sys_language table.
- Create a record for the language if necessary. The record should include the language name and code. The Active field should be set to true.
- Enable the language for the Now Assist model.
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- Go to the sys_generative_ai_model_config table and open the record for the model you want to add the language to, such as gpt_small by Azure OpenAI.
Note:The model for AI Search is named E5FT. If you want to make changes to the language support for AI Search, you can configure that record. After, you need to reindex all sources in the new language.
- In the Supported languages list, add the language and save the record.
- Go to the sys_generative_ai_model_config table and open the record for the model you want to add the language to, such as gpt_small by Azure OpenAI.
- Activate the language for Now Assist applications.
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- Go to and open the Multilingual service tab.
- Scroll to the provider you edited, then select the edit button.
- Select the language you added and save. Note:If you don't see your language as an option, ensure that the language is on the sys_language table and Active is set to true.
GlideCacheManager.flush("ais_semantic_embedding_model_cache");.Dynamic Translation
- Swedish
- Finnish
- Czech
- Hebrew
- Hungarian
- Korean
- Norwegian
- Polish
- Portuguese
- Russian
- Simplified Chinese
- Traditional Chinese
- Thai
- Turkish
- Arabic
- Danish
Choosing a translation service
Enabling translation for Now Assist
For more information on turning on multilingual services for Now Assist applications, see Enable translation for Now Assist applications.