What is this functionality?
This feature allows ClaudIA to automatically detect the user's language from the first messages of the conversation and start responding in that language — even if the project was originally set up with a different language.
It also allows you to:
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Set the project's default language (used as a fallback)
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Enable or disable automatic language detection
Why is this important?
Previously, ClaudIA always responded in the project's default language — except in some cases where the end user directly requested a change or, occasionally, when the language model (LLM), being non-deterministic, identified and applied the change on its own. However, this behavior was not controlled or reliable.
Now, with this functionality activated, the behavior is standardized, secure, and configurable, ensuring that ClaudIA's responses are consistently made in the most appropriate language for the user, whenever it can be identified with certainty.
What exactly is configurable?
By accessing the General Settings menu in the Hub, you can:
Enable automatic detection of the user's message language
- Default: enabled (when enabled by the operations team)
Project's default language
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Defines the language to be used when it is not possible to safely identify the user's language
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Default: Brazilian Portuguese
How does it work in practice?
➤ Automatic detection from the first messages
ClaudIA analyzes the first messages from the user to identify the language with the highest degree of certainty possible. If it is not possible to determine it with certainty right away, the system continues evaluating the following messages until it can identify it.
If one of the messages is sufficient — even if short — and the model has high confidence in the detection, ClaudIA will start responding in that language.
➤ Fallback to default language
While ClaudIA does not have sufficient confidence in the detection, it continues responding in the project's default language. This language is configured directly in the Hub.
➤ Deterministic behavior
Once the language is confidently identified, it becomes the primary language of the conversation, ensuring consistency and avoiding unexpected changes throughout the service.
💡 But it is worth reinforcing: this is the designed logic — that is, ClaudIA should continue responding in this language until the end of the conversation.
However, as it is a non-deterministic language model, the AI can still hallucinate or change the language in specific situations, especially if the user writes something very clear requesting a change (e.g., "now respond in English").
These cases are rare but possible. Therefore, although the standard behavior is stable, there are no absolute guarantees of 100% predictability.
Which projects can enable it?
This functionality is activated manually by the operations team and is available only for projects configured as multilingual.
By default, it comes with:
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Automatic language detection: enabled
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Default language: the same as the project's base language
If you wish to enable this functionality in your project, please contact the operations team.
Practical example
Suppose the project's default language is set to Portuguese:
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If the user sends:
"Hola, tengo una duda sobre mi plan"→ ClaudIA detects Spanish with high confidence and responds in Spanish. -
If the user sends:
"Hello"→ Short message, but if the model confidently detects it as English, ClaudIA responds in English. -
If the user sends:
"Oi"→ Not sufficient to guarantee language → ClaudIA responds in Portuguese (default language). -
If the user sends:
"Oi, gostaria de falar sobre meu plano"→ ClaudIA detects Portuguese with confidence and continues in Portuguese.
What is the only downside?
Language detection depends on the first messages of the conversation. If they are vague, ambiguous, or inconclusive, the system may end up using the default language — which is not an error, but may lead to a slightly less personalized experience.
📌 This is intentional to avoid incorrect translations based on few signals. The priority is to ensure safety in detection.
Best practices
🎯 General recommendation:
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Use this functionality only in multilingual projects.
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Correctly configure the default language to avoid inappropriate responses.
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Guide the support and curation teams about this behavior.
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Test in the Playground simulating different initial messages.