Vespa

Vespa is an open-source AI search platform that combines vector search, lexical search, and real-time machine learning inference in a single system. It enables organizations to build intelligent search and recommendation applications by co-locating vectors, metadata, and content on the same data node, eliminating traditional bottlenecks in AI-powered search workflows. The platform automatically handles data distribution across clusters and scales seamlessly from prototype to production, supporting billions of user interactions. The platform excels at powering use cases including semantic search, personalized recommendations, conversational AI, and real-time content ranking. Developers can deploy custom machine learning models and run inference directly alongside data, enabling split-second personalization at massive scale. Vespa's architecture is optimized for high-throughput, low-latency queries while maintaining strict relevance and ranking requirements. Vespa's fully open-source design means you can download and run it independently, or use the managed cloud service. The platform has proven itself in production environments serving hundreds of millions of users, handling traffic spikes and complex ranking logic without performance degradation. Its multi-search capability supports hybrid queries combining vector similarity with structured filtering and traditional keyword matching, providing flexibility for sophisticated retrieval strategies.