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Zilliz

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Zilliz is a fully managed Vector Lakebase platform built by the team that created Milvus, powered by Milvus under the hood, unifying real-time vector search, lake-scale discovery, and AI data operations. It goes beyond traditional vector databases by simultaneously providing real-time serving, iterative exploration, and batch analytics on a single data source, and can support data scales in the hundreds of billions. The platform is built on the team's deep understanding of failure modes in large-scale vector databases, validated over 8 years and by more than 10,000 enterprises in production; it can handle over 100 billion entities and more than 10,000 QPS while maintaining stable latency and predictable performance. Full data and indexes are stored in S3, combined with hot caching and on-demand compute, and are said to reduce costs by 90%. It supports multiple retrieval types such as vector, text, JSON, and geospatial, combined with hybrid retrieval, filtering, and reranking; it provides a tiered architecture, pay-per-query on-demand search, online backfill and schema iteration, and an access mode for building indexes directly on user S3 data (Iceberg, Lance, Vortex, Parquet), without copying or ETL. It is available in global regions on AWS, Google Cloud, and Azure.

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医真AI+

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Since its establishment, Yizhen AI+ has focused on the independent research, development, and application of underlying core technologies for comprehensive medical technology big data, including medical imaging, ultrasound, endoscopy, nuclear medicine, and pathology. It possesses highly advanced and mature applications in medical technology business, medical technology big data applications, collaboration, scientific research, operations, public perception, and artificial intelligence. As of now, it has served 2,500+ medical institutions.

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