The NeumAI team has developed technology to help keep context up-to-date and relevant for large-scale AI applications, particularly those using Retrieval Augmented Generation (RAG). This is crucial for building accurate chatbots on constantly changing data sources such as restaurant menus or team documentation. Neum's solution automatically synchronizes source data with a vector store, ensuring that the model always has access to up-to-date context. This approach is more efficient and cost-effective than constantly re-vectorizing data, especially when dealing with large datasets. By leveraging LangChain tools and detecting differences in data, Neum's technology can keep the context fresh without breaking the bank.