Key Features

Identify User Intents

Stay on topic Maintain natural dialog flow for your customers by precisely identifying user intents using both LLMs leveraging XO GPT and traditional ML models.

• Keep your options open: Use a multi-engine NLU for optimal accuracy.
• Make it custom: Leverage fine-tuned models for contact center conversational use cases.
• Stay on topic: Maintain conversational context across turns in dialog flow.

Provide Empathetic Responses

Be informative and kind Enhance responses by combining general-purpose LLM with domain-specific information in an empathic and contextual manner.

• Show empathy: Adapt dialogs based on user sentiment.
• Be flexible: Handle digressions and interruptions gracefully using coreference resolution.
• Get personal: Personalize responses with generative AI for natural interactions.

Multi-language Support

Speak their language Interact with customers and employees around the globe with more than 100 languages supported.

• Think global: Scale IVAs across multiple languages.
• Don’t get lost in translation: Carry over dialog definitions in another language, even if you don’t speak it with built in translation.
• Be adaptable: Create an NLP model for any language.