Your AI Database Works at Production Scale
Build RAG, semantic search, AI agents, and next-gen AI applications with the world's most popular vector database. Trusted by 10,000+ enterprises globally for billion-scale AI workloads.
Zilliz Cloud
Fully-managed vector database service designed for speed, scale and high performance.
VectorDB Benchmark
Open-source benchmark designed from the ground up to test AI databases under real production conditions.
Why Zilliz Cloud is the Top Chioce for Enterprise-Level Vector Search and AI Workloads.
Why Zilliz Outperforms Traditional Databases for AI Workloads
Zilliz Cloud is a purpose-built AI database with unmatched scale and performance, cost efficiency, and enterprise security.
Natural Language as Infrastructure
Manage your entire vector database through conversational AI. Our MCP server lets you perform complex operations using natural language in Claude, Cursor, and Windsurf—no manual queries needed.
10x Faster with AI-Powered Search
Zilliz Cloud offers an AI-powered Cardinal Search Engine, delivering over 10x performance boost compared to alternatives, with millisecond latency even at billion-scale vector operations.
Deploy in Minutes with 0 Vendor Lock-in
Fully managed service of Milvus, the world's most popular open-source vector database, eliminates DevOps overhead. From prototype to production without managing infrastructure or vendor lock-in.
Seamlessly Integrate Your AI Stack
Choose from our growing ecosystem of 100+ integrations for LLMs, embedding models, data ingestion, visualization, language clients, and more. Works with your existing tools.
Up to 70% Lower TCO
Cost-optimized compute units and automated storage tiering slash infrastructure costs. Pay only for what you use with serverless scaling.
Enterprise-Grade Security & Global Scale
SOC 2 Type II, ISO 27001, GDPR, HIPAA, and PCI compliant with advanced RBAC, multi-tenancy, private networking, and BYOC. Deploy across 26 global regions on AWS, GCP, or Azure with complete data sovereignty.
Power Every AI Use Case
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RAG (Retrieval Augmented Generation)
Enhance LLMs with your private data for accurate, contextual responses
AI Agents & Chatbots
Build intelligent agents with real-time knowledge retrieval
Semantic Search
Find relevant content by meaning, not just keywords
Recommendation Systems
Deliver personalized experiences based on user behavior
Image/Video/Audio Search
Search multimedia content by similarity and semantic meaning
Fraud Detection
Identify anomalies and patterns in real-time transactions
Built on Milvus. Loved by Developers. Trusted by Enterprises.
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See what our customers are saying
We were running a multilingual RAG system at scale, indexing all of Wikipedia into tens of millions of high-dimensional vectors. Latency targets were tight. We needed a system that could handle real-time retrieval over millions of knowledge vectors without breaking under load. Zilliz gave us that. It freed up engineering cycles and let us focus on improving reasoning on the model side, not managing infrastructure. That reliability mattered because we were operating at 3,500+ dimensions per vector, across a fast-growing corpus, with sub-300ms latency requirements in production. "
Dr. Pratyush Kumar
Co-Founder of Sarvam
Milvus has done an extraordinary job in revolutionizing Likee's video deduplication system, which significantly fueled the growth of BIGO's short-video business."
Xinyang Guo
Software Engineer at BIGO
We've gained so much from the Milvus community that we decided to contribute features like "hot reload," which have also benefited our internal operations."
Dennis Zhao
AI Infrastructure Lead at SmartNews
When we identify a need for specific data, we can often find the required data in our database the same day using text or image search with Milvus. This greatly improves our data processing efficiency and has a positive effect on our business operations."
We have the full end-to-end data... law as a timeline. We have the incident, the start, everything that's happening, and the conclusion of the case. There's an enormous amount of power in having that all within the work system."
Brianna Connelly
AI Team Lead at Filevine
We've got millions of monthly active users and all of the underlying data when we're trying to go find related conversations, find updates to an action item, find referenced documents...Milvus serves as the central repository and powers our information retrieval among billions of records."
What we wanted was to push intelligence to the user before they even asked. Milvus is what made that viable."
Choosing Zilliz Cloud was one of our best early decisions. It enabled us to build the product we envisioned rather than the product our infrastructure limitations would allow. In AI applications, that difference often determines success or failure."
Ethan Zheng
Co-Founder & CTO of Jobright.ai
We were running a multilingual RAG system at scale, indexing all of Wikipedia into tens of millions of high-dimensional vectors. Latency targets were tight. We needed a system that could handle real-time retrieval over millions of knowledge vectors without breaking under load. Zilliz gave us that. It freed up engineering cycles and let us focus on improving reasoning on the model side, not managing infrastructure. That reliability mattered because we were operating at 3,500+ dimensions per vector, across a fast-growing corpus, with sub-300ms latency requirements in production. "
Dr. Pratyush Kumar
Co-Founder of Sarvam
Milvus has done an extraordinary job in revolutionizing Likee's video deduplication system, which significantly fueled the growth of BIGO's short-video business."
Xinyang Guo
Software Engineer at BIGO