Our client, a Medicare insurance broker, came to us looking to streamline his customer service processes using artificial intelligence. As customers often find it difficult to find, retrieve, and interpret pieces of important information within Medicare documentation and contracts, our client approached us to create a solution; we happily obliged.
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.
What We Did
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.
Combined GPT and LLaMA Technology
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.