Zilliz
Zilliz is on a mission to unleash data insights with AI. The company builds next-generation database technologies to help organizations rapidly create AI/ML applications and unlock the potential of unstructured data.
Founding Story
Zilliz was founded in 2017 in Shanghai, China by Charles Xie (who goes by the nickname Starlord). The company was built by the engineers who created Milvus, the world's most popular open-source vector database. Zilliz's journey started with the creation of Milvus in 2019, which eventually joined the LF AI & Data Foundation as a top-level project.
Discussions
No discussions yet
Be the first to start a discussion about Zilliz
Leadership
Founders
Charles Xie
Previously worked as a software engineer at Oracle in the U.S. where he was one of the founding engineers of the Oracle 12c cloud database project. Before that, he was a Software Engineer Intern at Cisco. Charles holds a master's degree in computer science.
Executive Team
Charles Xie
Founder & CEO
Previously founding engineer of Oracle 12c cloud database project. Holds master's degree in computer science. Also known by nickname 'Starlord'.
James Luan
VP Engineering
Business Model
Revenue Model
SaaS subscription and usage-based pricing for managed cloud services (Zilliz Cloud), with enterprise licenses and support contracts. Revenue generated through API usage, compute units (vCUs), storage, and data transfer. Also offers BYOC (Bring Your Own Cloud) for custom deployments.
Pricing Tiers
Starting point for learning and personal projects. 5 GB storage. 2.5M vCUs per month included. Up to 5 collections.
Managed essentials for non-critical workloads. Best for prototypes and testing environments. Fully managed vector databases with core APIs. Backup, restore, and basic monitoring. Built-in encryption for data in transit and at rest.
Managed essentials for non-critical workloads with dedicated resources.
Enterprise-grade reliability and controls for production applications. 99.95% uptime SLA. Audit logs, SSO (SAML 2.0), granular RBAC. Multi-replica and elastic scaling. Private endpoint and VPC peering. Enterprise support included.
Regulated-ready with maximum resilience for healthcare, finance, and highly regulated systems. Global cluster with high availability and disaster recovery. Advanced security with CMEK and full-path encryption. HIPAA-eligible. Priority support and rapid incident response.
Deploy on your own infrastructure with enhanced data protection and compliance. Same features as SaaS Dedicated clusters.
Ideal for real-time applications. 1.5M vectors per CU. 500-1500 QPS. 10ms latency.
For large vector datasets with reliable speeds. 5M vectors per CU. 100-300 QPS. 50-100ms latency.
Ultra-large-scale, cost-sensitive workloads. 20M 768-dim vectors per query CU. Hot data: 100-150 QPS, 20-40ms latency. Cold data: 5-20 QPS, 200-1000ms latency.
Target Markets
- Enterprise AI and ML application developers
- Technology companies building AI/LLM applications
- E-commerce and retail (product search and recommendations)
- Financial services and fintech
- Healthcare and life sciences
- Legal technology
- Real-time vector search for AI applications
- Similarity search and recommendations
- Image and video search and deduplication
- Semantic search and natural language processing
- Conversational AI and chatbots
- RAG (Retrieval Augmented Generation) for LLMs
- NVIDIA
- PayPal
- AT&T
- Walmart
History & Milestones
Raised $400M funding round
Selected AWS as strategic cloud provider
Achieved AWS Agentic AI Specialization
Milvus reached 33,000 GitHub stars and exceeded 100 million downloads and deployments
Published research at VLDB 2022
2 AI Tools by Zilliz
Zilliz Cloud
20dFully-managed vector database service built on Milvus, designed for speed, scale, and high performance AI applications.
Milvus
2moAn open-source vector database built for GenAI applications with high-speed searches and scalability to tens of billions of vectors.
