The company is focused on developing AI applications by managing indices effectively and creating vectors from raw content through machine learning, rather than relying on legacy systems designed for large-scale web applications with billions of vectors. They aim to simplify the process for developers by making the embedding model transparent and easy to use, offering default local models and options to integrate with external APIs using simple steps. The goal is to empower AI application developers to build robust applications without needing specialized infrastructure engineers or data scientists, and the company has recently received its first round of seed funding to support these efforts.