Vinted moves from Elasticsearch to Vespa | Vespa Blog
With Vespa, Vinted managed to halve the number of servers, slash query latency by 2.5x, indexing latency by 3x, and increase ranking depth by more than 3x.| Vespa Blog
With Vespa, Vinted managed to halve the number of servers, slash query latency by 2.5x, indexing latency by 3x, and increase ranking depth by more than 3x.| Vespa Blog
According to ESG, 41% of retail respondents in a 2024 survey are either already pursuing or planning to pursue AI-powered product recommendations.| Vespa Blog
AI search requires more than a vector database. A search platform bridges the gaps.| Vespa Blog
Perplexity chose to build on Vespa.ai to provide the world’s most used RAG application.| Vespa Blog
Improvements made to triple the query performance of lexical search in Vespa.| Vespa Blog
Tutorials on feeding data to Vespa from CSV files, PostgreSQL, Kafka, Elasticsearch and another Vespa.| Vespa Blog
Advances in Vespa features and performance include Elasticsearch vs Vespa Performance Comparison, Vision RAG and Binarizing Vectors| Vespa Blog
Discover how Vespa outperforms Elasticsearch in query efficiency, scalability, and operational costs, making it a robust choice for modern eCommerce search solutions.| Vespa Blog
This AI-driven ecommerce evolution is driven by consumer’s increasing demand for personalized experiences, real-time interactions, and seamless omnichannel integration.| Vespa Blog
