From a vast array of available large language models, we select the most fitting large language models (LLMs) to meet specific use cases, ensuring precision and relevance. Our unique two-tier training process, involving both curated public and specialized non-public data, equips our AI assistants with unparalleled accuracy and skill. Our proprietary algorithms create a response score for each interaction to track the response fidelity and minimize hallucinations. It also enables frictionless retraining on a per response basis delivering AI employees are constantly learning, improving and staying away from hallucination issues typical of publicly available LLMs.

Our custom application layers generate AI assistants that are not just knowledgeable on a topic but are also capable of creating personalized experiences for each user based on all past interactions. Seamless voice and chat based authentication layers recognize the user. The natural language parameter recognition layer automatically recognizes when a parameter of interest is mentioned the conversation. The recognized parameters are securely packaged and stored in user specific fields of our highly secure databases. The function layers can perform numerous functions on the stored data from visual display to being recalled in a future voice conversation.

Post deployment, our ConversAI capability performs a deep analysis of interaction data. It meticulously analyzes conversational and interaction data from various digital touch points. By delving deep into the nuances of customer communications, ConversAI Insight identifies patterns, sentiments, and behaviors, offering unparalleled insights into customer preferences and expectations. Based on this analysis, it generates actionable recommendations to refine and up train the AI assistant on targeted key performance indicators of interest - such as improved customer satisfaction or client conversions.