Conversational AI, also known as chatbots, are powered by natural language processing (NLP) and machine learning (ML) technologies. We leverage OpenAI's NLP capabilities which allow chatbots to understand and respond to human language in a natural way. This includes the ability to understand the meaning of words and phrases, as well as the ability to generate text that is grammatically correct and semantically meaningful.
We are leveraging OpenAI's NLP and ML capabilities to make the Conversational AI systems flexible and cognitive. OpenAI's GPT models are capable of generating text that is almost indistinguishable from text written by humans and enabling chatbots to generate natural and engaging conversations.
ThirdEye Data builds advanced Conversational AI systems for enterprises to execute natural, relevant, semantic and engaging conversations though chatbots.
We have prepared smart Conversational AI models which are ready to be deployed.
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Before leveraging the conversational AI systems, businesses may have some common asks. We are trying to answer them here.
The chatbot's NLP engine works by breaking down the user's input into smaller units of meaning, such as words, phrases, and entities. The engine then uses these units of meaning to identify the user's intent and to generate a response.
The chatbot handles complex queries by using a combination of NLP techniques, such as semantic parsing and machine reasoning. These techniques allow the chatbot to understand the meaning of complex queries and to generate accurate and relevant responses.
The chatbot can integrate with existing CRM system by using a variety of APIs. This allows the chatbot to access customer data from the CRM system and to use this data to generate more personalized responses.
You can measure the success of the chatbot by using a variety of metrics, such as customer satisfaction, lead generation, sales, and cost savings. These metrics can help you to track how the chatbot is performing and to identify areas where it can be improved.
The cost of developing and deploying a chatbot will vary depending on the complexity of the chatbot, the features that are included, and the development team that is used.
The chatbot's accuracy rate depends on a number of factors, including the quality of the training data, the complexity of the queries, and the design of the NLP engine. However, in general, chatbots can achieve accuracy rates of over 90%.