10x Your RAG Development Speed with Vectorize for Zilliz
We’re excited to announce Vectorize now integrates with Milvus and Zilliz Cloud! 🎉
Milvus is an open-source vector database that makes it easy to store, search, and retrieve vector data, making it an excellent choice for retrieval-augmented generation (RAG) applications. Zilliz Cloud is the fully managed service of Milvus, and offers enterprise-grade performance and scalability. Vectorize’s integration simplifies the process of getting high-quality embeddings into your vector database, and keeps them updated as your data evolves.
Vectorize supports either fully-managed Milvus on Zilliz Cloud, or a self-hosted Milvus instance that’s accessible through a public network.
The Complexity of Building RAG Pipelines
Getting your data into your database can be complicated, tedious, and time consuming. You need to extract unstructured data from one or more sources, then preprocess it to make sure it’s clean, consistent, and well-structured. Selecting the right embedding model and vectorization strategy is critical, but it’s often difficult to tell which approach is best for your data; choosing an approach can involve trial and error and guesswork. Once you’ve selected your approach, you need to generate embeddings and load them into your database. As your data evolves, you need to continually update your vector indexes to ensure they’re fresh, so your AI application returns accurate, relevant results. The higher the data quality, and the more up-to-date your indexes are, the better your RAG application will perform.
Vectorize Simplifies RAG Pipelines
Vectorize makes it fast and easy to create and maintain RAG pipelines that not only populate your vector database, but also keep your embeddings updated as your source data changes. Before deploying your pipeline, you can evaluate different models and vectorization strategies on a subset of your own data, allowing you to make a data-driven decision on which approach to use.
To create a pipeline you specify one or more data sources, select the AI platform you want to use, choose the embedding model and vectorization strategy, then deploy. Vectorize handles everything else for you—it processes your data, loads it into Milvus or Zilliz Cloud, and automatically updates your vector indexes so your application always has access to the most current and relevant embeddings.
Zilliz and Vectorize: Built for AI Engineers
Milvus and Zilliz Cloud deliver reliable vector storage and high-performance vector search. Vectorize automates your RAG pipelines, continuously updates and optimizes the vector indexes, ensuring your LLM always has the latest data and delivers the most relevant results. The combination allows you to focus on creating your AI application instead of on building and managing pipelines.
Getting Started
Ready to try it out? Sign up for the Vectorize platform, connect your Milvus or Zilliz Cloud instance, and deploy your first RAG pipeline in minutes.