# Overview Please note most of these use cases are voice-centric, we see voice conversations as an initial opportunity. However, vCon works for conversations across any communications media, e.g. email, video, SMS, web chat, social, chat in IP messaging like WhatsApp, etc. Think of vCon as ‘robot food’, enabling conversation data to be presented in a common format and more easily cleaned for training of machine learning. ASR and conversation AI solutions do not meet the needs of some businesses with respect to accuracy, vCon will help our industry close the gap with respect to the hype. The performance of ASR varies greatly depending on the application, quality of the recording, and engine/training. ASR continues to improve, some of these applications could be a stretch for a legacy call center, however, for some scenarios they are attainable today. \\ \\ --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://www.conserver.io/use-cases-studies/overview.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.