Project Overview
WayWay uses a large MongoDB Atlas Database of places data, connected to the backend via a Flask API. Queries to the database are made using MongoDB Atlas Vector Search, using OpenAI vector embeddings to find similar places to the user's preferences. LangChain and OpenAI are used to extract novel information from the returned places documents, such as the sentiment of the reviews, and the sentiment of the place's description. This information is then used to provide the user with a more personalised experience according to their preferences.
The team is comprised of 4 members, with myself as the lead AI engineer. I am responsible for the AI and ML aspects of the project, including the development of the AI models, and the integration of the AI models into the backend. We are actively developing our concept, learning new skills and networking with potential investors and partners, and hope to release a demo in the coming months.