How Garden Scaled Patent Intelligence with Qdrant

Garden, a New York-based startup, has transformed patent intelligence by using Qdrant's filterable vector search to efficiently analyze the vast global patent corpus of over 200 million patents. This innovative approach allows Garden to quickly match patents with products using a sophisticated AI system, addressing the limitations of traditional manual analysis. Initially, Garden faced challenges with high costs and inefficient filtering in their original vector search solutions, prompting them to transition to Qdrant. Qdrant's managed Rust-based infrastructure and filterable HNSW feature enabled Garden to achieve sub-100ms query latency and store significantly more data at a reduced cost. This transformation allowed Garden to launch a new line of business focused on high-confidence infringement detection, providing clients with rapid, claim-chart quality analyses. As Garden continues to grow, it plans to enhance its patent analysis capabilities by further enriching patent data, thereby focusing on delivering valuable intellectual property insights to its customers.