Zilliz Cloud Pipelines
Vectorize with Ease, Turning Unstructured Data Searchable
What is Zilliz Cloud Pipelines?
Simplify and streamline the conversion of unstructured data into state-of-the-art vector embeddings, which are then stored in the Zilliz Cloud vector database for efficient indexing and retrieval.
Simplify the workflow for developers
Developers often face the complexity of converting and retrieving unstructured data, slowing down development. Zilliz Cloud Pipelines addresses this challenge by offering an integrated solution that effortlessly transforms unstructured data into searchable vectors, ensuring high-quality retrieval from vectorDB.
View RAG Building Example NotebookDeliver Excellence across All Stages of Vector Search Pipelines
Creating high-quality vector pipelines from unstructured data involves nuanced processes such as parsing and cleaning data, embedding, ANN searching. Built by AI experts, Zilliz Cloud Pipelines are designed to master these complexities end to end, guaranteeing superior quality at each stage despite the level of expertise.
Ensure scalability for large datasets and high-throughput queries
Developers often encounter challenges in scaling large datasets and high-throughput queries while preserving performance. Zilliz Cloud Pipelines addresses this by providing built-in scalability and high performance, eliminating the need for extensive customization or infra modifications, ensuring efficient data handling.
Capabilities
Vector Conversion
Simplify the conversion of unstructured data into searchable vector embeddings. Support functions range from creating vector embeddings for document chunks to preserving metadata for retrieval during searches.
Semantic Search
Efficiently convert query text into vector embeddings, delivering the top-K most relevant document chunks with text and metadata. Discover meaningful search results quickly and effectively.
Filter with Metadata
Enhance search capabilities by filtering with pre-defined metadata. Pipelines support everything from refined searches of raw vectors to leveraging stored metadata for precise query results.
How does Zilliz Cloud Pipelines work?
View DocumentationFrequently Asked Questions
How can Zilliz Cloud Pipelines enhance my semantic search capabilities?
Which Zilliz Cloud Product Tiers are Pipelines available in?
Which embedding model does Zilliz Cloud Pipelines use?
How is Zilliz Cloud Pipelines charged?
Can I use Zilliz Cloud Pipelines standalone?
What data sources are supported by Ingestion Pipelines?
What document file formats are supported by Pipelines?