Vectorize is an AI tool designed to turn unstructured data into optimally structured vector search indexes. This technology is built for Retrieval Augmented Generation, meaning it operates on the principle of retrieving and utilising relevant information to improve AI task performance. Vectorize can be used in a variety of applications such as question answering systems, AI copilots, call center automation, content automation, and hyper-personalization. The tool involves a three-step process comprising import, experiment, and deploy. During the import phase, users can upload documents or link to external knowledge management systems from which Vectorize extract natural language for AI use. The experiment phase involves determining the most beneficial chunking and embedding strategies. Once a vector configuration is selected, it can be converted into a real-time vector pipeline through the deploy phase. This pipeline can automatically update when changes in data occur, thereby ensuring high accuracy. Vectorize includes built-in support for various AI platforms such as Hugging Face, Google Vertex, LangChain, AWS Bedrock, OpenAI, Microsoft Azure, Jina AI, Voyage AI, and Mistral AI. It also offers automatic creation and updates of vector indexes in a user's favorite vector database. Vectorize automates the process of turning data into AI-ready vectors, which can then be stored into a user's selected vector database.