Abstract: A method and/or system for dynamic generation of personalized video content in a conversational interface is disclosed. A chat application at a client device receives input from user which is communicated to chatbot platform. The chatbot platform composes a response in a data package and communicates to the chat application. If the format of the data package is of the type ‘Personalized Smart Video’, then a personalized video generation engine may generate a personalized video using a video template by displaying the video template and dynamically overlaying transformed user data on top of dedicated placeholders in the video template, thereby enhancing the user experience by rendering messages in form of personalized video at the client device and eliminating the need of creating a separate video file for each target user.

Abstract: Provided is a method and system for performance evaluation using an AI model comprising automatic extraction of accurate call disposition details from the interactions for any domain, so that interactions can be tagged consistently and accurately, and actionable insights can be derived, by training AI models. It provides a method and system that can be used in real time for automating the call disposition detailing for any conversation over a call. In an example the call conversation may be a customer care call, or any other work-related call. It may allow users to extract issues, cause and resolution from a call transcript with utmost accuracy, also train it further on client specific data. The extracted text is then used to for performance evaluation using multiple KPIs and parameters.

Abstract: A method and/or system for dynamic generation of personalized video content in a conversational interface is disclosed. A chat application at a client device receives input from user which is communicated to chatbot platform. The chatbot platform composes a response in a data package and communicates to the chat application. If the format of the data package is of the type ‘Personalized Smart Video’, then a personalized video generation engine may generate a personalized video using a video template by displaying the video template and dynamically overlaying transformed user data on top of dedicated placeholders in the video template, thereby enhancing the user experience by rendering messages in form of personalized video at the client device and eliminating the need of creating a separate video file for each target user.