Leveraging our knowledge of AI model development and prompt engineering, we built our client an AI chatbot system that allows users to conveniently search through Medicare insurance documents, retrieve information, and even have it explained in simple terms. This was done by integrating hardened ChatGPT and LLaMA technology in our highly-secure user interface, solving the client’s issue with an extra focus on security.
We built a user-friendly interface similar to that of social media messaging windows or existing AI chatbots like ChatGPT, enabling customers to easily type and send requests to the chatbot using a conversational-like flow. This way, requests and functionality feel as natural as speaking with a live customer service agent.
Medicare insurance documents can be lengthy, making AI processing and responses times inconvenient. As a result, we used a technique called AI embedding in order to represent data in a way that’s easy for machine algorithms to understand. In this case, we used Meta’s AI Model, LLaMA, and its indexing capabilities to retrieve digestible sections of the insurance documentation and feed it to our AI chatbot.
We used a combination of OpenAI’s GPT and Meta’s LLaMA AI technology to create a powerful system that can swiftly find and retrieve information, while also returning human-like conversational responses.
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