2025-06-17 –, Palais Atelier
Modern search demands scalable personalization. Discover Vespa’s multi-stage ranking and tensor framework for hybrid queries, multimodal retrieval and real-time ML Learn how to deploy low-latency, high-relevance search systems at petabyte scale.
Today’s applications require search engines to unify text, vectors, and business logic with millisecond latency at petabyte scale. It’s not easy to balance speed, relevance, and personalization for a large user population and a billion scale item base. Vespa.ai, the open-source engine powering Yahoo, Perplexity, Qwant, Vinted, Spotify addresses this through multi-stage ranking with close to data tensor operations and easy to understand custom functions.
Vespa’s phased architecture enables high performance due to the ability to filter candidates via hybrid retrieval (text + multi vector + filters) before applying ML models for precision or logic for personalisation. Its tensor framework enables multimodal (text/image/video) and multivector queries with real-time individual personalization, scaling beyond 100k QPS with milliseconds latency.
You will learn Vespa.ai configuration concepts and ideas how all the building blocks (LLMs, VLMs, embedding models, sparse and dense representations for items and users) can be connected together.
This session is sponsored by Vespa.ai.
Search
Level:Intermediate
Piotr Kobziakowski is a Senior Principal Solutions Architect at Vespa.ai, where he leverages over 20 years of expertise in software architecture, network security, big data, and search technologies to design scalable AI-driven solutions for global enterprises. Based in Warsaw, Poland, he specializes in advising organizations on data, analytics and search applications.
Prior to joining Vespa.ai in October 2024, Kobziakowski held progressive technical roles at Elastic, where he architected search and analytics solutions for telecommunications. His career spans across industry leaders like Akamai, Nominum, Cloudmark and Bytemobile, with a focus on optimizing large-scale data and analytics infrastructure and security systems.
Piotr’s approach combines hands-on technical advisory with strategic problem-solving,
through delivering workshops and customized training programs. He is recognized for translating complex technical concepts into actionable roadmaps, enabling enterprises to operationalize technology capabilities. A frequent speaker at many events related to GenAI, Data and Analytics.