AI BriefingMiricanvas Introduces Dual Vector Search and Performance Optimization Using Amazon OpenSearch Service
Key point
Miricanvas introduced dual vector search based on Amazon OpenSearch Service for 40 million design resources and optimized performance.
Details
Miricanvas introduced a Dual Vector design to provide semantic search for its vast collection of 40 million design resources. Through this, they built a search experience that more accurately captures user intent.
During implementation, they utilized Amazon OpenSearch Service (v2.19) and focused on resolving the memory and IOPS bottlenecks that occur when processing large-scale data. In particular, they optimized index structure and resource allocation to improve the efficiency of vector search.
The key achievements and technical challenges are as follows:
- Semantic search: Applied a dual vector model combining text and image features
- Performance optimization: Resolved memory management and IOPS bottlenecks in the OpenSearch environment
- Scalability: Designed an architecture to reliably process large-scale design resources
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