Using Jev as a search reranker: benchmarks and how to implement
Elasticsearch Labs
Using Jev as a search reranker: benchmarks and how to implement
We had Jev score Elasticsearch hybrid search results and let a short Python policy do the reranking, taking nDCG@10 from 0.9351 to 0.9565 on 250 Amazon Shopping Queries, and the code is all here.
Elasticsearch Vector Database: Ship in minutes, scale affordably to hundreds of billions
Elasticsearch Labs
Elasticsearch Vector Database: Ship in minutes, scale affordably to hundreds of billions
The hard parts of hybrid retrieval, already done, with optimized defaults, third party and native Jina AI models, and managed GPU inference all out of the box. Build fast, scalable AI apps, not infrastructure.