Agent Search on Gemini Enterprise Agent Platform
Agent Search on Gemini Enterprise Agent Platform is a powerful solution designed to deliver Google-quality search experiences using enterprise data. It enables developers to build advanced search systems for websites, structured datasets, and unstructured content quickly and efficiently. The platform enhances traditional keyword search by introducing conversational, generative AI-powered search capabilities. It also serves as an out-of-the-box retrieval augmented generation (RAG) system, improving the accuracy and relevance of AI-generated responses. Agent Search simplifies complex processes like data ingestion, indexing, and retrieval into a streamlined workflow. It supports industry-specific use cases, including healthcare, media, and commerce, with tailored search capabilities. Developers can further customize solutions using APIs for embeddings, ranking, and grounded generation. Overall, it helps organizations transform how users discover and interact with information.
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Zilliz Cloud
Zilliz Cloud is a fully managed vector database based on the popular open-source Milvus. Zilliz Cloud helps to unlock high-performance similarity searches with no previous experience or extra effort needed for infrastructure management. It is ultra-fast and enables 10x faster vector retrieval, a feat unparalleled by any other vector database management system. Zilliz includes support for multiple vector search indexes, built-in filtering, and complete data encryption in transit, a requirement for enterprise-grade applications. Zilliz is a cost-effective way to build similarity search, recommender systems, and anomaly detection into applications to keep that competitive edge.
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Pinecone
The AI Knowledge Platform.
The Pinecone Database, Inference, and Assistant make building high-performance vector search apps easy. Developer-friendly, fully managed, and easily scalable without infrastructure hassles.
Once you have vector embeddings, manage and search through them in Pinecone to power semantic search, recommenders, and other applications that rely on relevant information retrieval.
Ultra-low query latency, even with billions of items. Give users a great experience. Live index updates when you add, edit, or delete data. Your data is ready right away. Combine vector search with metadata filters for more relevant and faster results.
Launch, use, and scale your vector search service with our easy API, without worrying about infrastructure or algorithms. We'll keep it running smoothly and securely.
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Qdrant
Qdrant is a vector similarity engine & vector database. It deploys as an API service providing search for the nearest high-dimensional vectors. With Qdrant, embeddings or neural network encoders can be turned into full-fledged applications for matching, searching, recommending, and much more!
Provides the OpenAPI v3 specification to generate a client library in almost any programming language. Alternatively utilise ready-made client for Python or other programming languages with additional functionality.
Implement a unique custom modification of the HNSW algorithm for Approximate Nearest Neighbor Search. Search with a State-of-the-Art speed and apply search filters without compromising on results.
Support additional payload associated with vectors. Not only stores payload but also allows filter results based on payload values.
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