Azure Cosmos DB Vector Search
Enterprise vector search with Azure Cosmos DB. We implement semantic search and RAG solutions using Cosmos DB's native vector capabilities for globally distributed, low-latency AI applications.
Overview
Azure Cosmos DB's vector search capabilities enable semantic search and RAG at global scale. Our implementations leverage this technology for enterprise knowledge bases, product discovery, and intelligent document retrieval.
Our Approach
We design vector search architectures that combine Cosmos DB's global distribution with efficient embedding strategies. Our solutions include hybrid search combining vector similarity with traditional filtering for optimal results.
Expected Outcomes
Organizations achieve sub-10ms semantic search globally, unified data and vector storage, and seamless integration with Azure OpenAI for RAG. Our Cosmos DB vector implementations scale to billions of vectors with consistent performance.
Key Capabilities
- DiskANN index optimization
- Hybrid vector and property filtering
- Multi-region vector replication
- Embedding pipeline integration
- Change feed for real-time vector updates
Ready to Get Started?
Our team of enterprise AI specialists is ready to help you implement azure cosmos db vector search that delivers measurable business results.