One of the biggest drawbacks of only using machine learning to build conversational AI applications is the staggeringly large amounts of data required to understand humans. What comes naturally to us, the relationships between words, phrases, sentences, synonyms, lexical entities, concepts etc., must be learned by a machine. For enterprises that don’t have a significant amount of relative and categorized data readily available, this is a costly and time-consuming part of building conversational AI applications.
Teneo Languages allow enterprises to teach new conversational applications all the possible language permutations in a matter of moments. Our Teneo NLU Ontology and Semantic Network, map the very structure of language itself, removing one of the most costly and time-consuming parts of building conversational AI applications — teaching a machine to understand human language. Therefore, the user simply enters a few representative queries, and Teneo Languages will enable the application to learn all the different ways a user might ask the same exact question.
Because Teneo is available in over 40 languages, you can deliver geo-specific conversational AI applications with the feel of a consistent global brand. Teneo Languages enable the application to ‘think’ in your native tongue, while delivering the same linguistic sophistication across every other language required. Our technology allows enterprises to share the core knowledge across all deployments whilst retaining the ability to adapt local implementations for different business processes.
Being able to develop your next CAI solution in over 40 languages is already an advantage but making the process easier and faster is a game changer. This is where our Teneo Linguistic Modeling Language comes in; our proprietary syntax language enables non-linguist developers to skip several steps in a typical build process. This unique and powerful modeling language automatically applies language conditions such as understanding when the word book is used as a noun or verb in a sentence, recognizing sentiment or providing a safety net to further ensure a humanlike conversational experience in the final product.
Developers can also use our conversational modules, which deliver pre-built solutions with back-end integration for common dialogues such as live chat handover or booking a meeting room, have also been released. These support the wide range of existing pre-built conversational knowledge that enables the chatbot to have a personality, continue the conversation even when the user has gone silent, maintain a personality that aligns with the enterprise’s brand values and keep the momentum going even when the user goes off topic. Just tick a box and they are readily available in your solution.