Cognigy.AI Docs

COGNIGY.AI is the Conversational AI Platform focused on the needs of large enterprises to develop, deploy and run Conversational AI’s on any conversational channel.

Given the arising need of voice interfaces as the most natural way of communicating with brands, Cognigy was founded in 2016 by Sascha Poggemann and Phil Heltewig. Our mission: to enable all devices and applications to intelligently communicate with their users via naturally spoken or written dialogue.

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Language Support

Learn about Languages supported by Cognigy AI

Overview of supported Languages

Cognigy.AI's on-board NLU is pre-trained with curated data from over 100 languages to support intent recognition and keyphrase detection. Any other natural (or artificial) language is supported based on language-agnostic NLU algorithms.

For 20 of the most common languages, Cognigy.AI provides prebuilt entities that allow automatic processing of inputs like dates, currencies and others specific to a language that is defined in the flow.

  • Generic (see below)
  • Danish
  • English (Australia)
  • English (Canada)
  • English (India)
  • English (UK)
  • English (US)
  • German
  • Japanese
  • Korean
  • Spanish
  • Dutch
  • Arabic
  • Finnish
  • French
  • Italian
  • Norwegian
  • Polish
  • Swedish
  • Thai
  • Chinese
  • Vietnamese
  • Portuguese - Brazil

Generic Language

The Generic Language allows you to do Intent mapping in any language which, along with Keyphrase detection and our powerful Rule Intent Engine, enables you to build Flows in any language.


The Generic Language uses multi-lingual NLU algorithms and models. This must be qualified to include only space-tokenized languages such as English for full support. E.g., keyphrase detection uses spaces " " as a delimiter. Intent mapping works across tokenization schemes but also benefits from space-tokenized languages.

Rule Intents with the Generic Language

A powerful and useful way to use the Generic Language is by using Rule Intents. These Intents lets you define custom rules using CognigyScript that will decide whether the Intent is triggered. You can thereby have a rule like this:

  •[0].keyphrase === "pizza"

Which means that as soon as the user mentions the word pizza, this Intent will be triggered. For more information on how to use these Intents, please go here.

Adding positive and negative confirmation words

For our askYNQuestion Nodes to work, we need to know which words are positive confirmations, and which words are negative confirmations. For instance, if you use English as a language, then we know that if the user answers "yes", then we will trigger the onYes part of the askYNQuestion Node. However, since you are essentially using any language by using the Generic language, we don't have this information. You therefore need to open the FlowProperties panel in your Flow and navigate to settings. Here are two settings called "Additional confirmation words" and "Additional negative confirmation words". The first one is a list of words that should trigger the onYes part of an askYNQuestion Node, whereas the second one is a list of words that should trigger the onNo part of an askYNQuestion Node. You simply write the list of words as a comma seperated list (e.g. yes, correct, ok). You can also use these to extend the confirmation words for other languages.

Updated 14 days ago

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Language Support

Learn about Languages supported by Cognigy AI

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