Daniel Svonava
Daniel is the CEO & co-founder of Superlinked.com, an ML infrastructure platform for building intelligent search, personalization and analytics experiences with vector embeddings that combine structured and unstructured data. Previously, Daniel was an ML Tech Lead at YouTube, where he built ads forecasting infrastructure that powered the buying flows of $10B/y-worth of ads. Today, Superlinked works with customers with millions of data points and daily queries and Daniel will share learnings from taking these projects from POC to Production - including evals, A/B tests, complex integrations, how to enable the customer's product & internal teams to solve business problems quickly with vectors and how to enable agentic workflows with retrieval as a tool.
Speaker Sessions
Your Marketplace Needs Vector Embeddings That Combine Structured, Unstructured & Behavioral Data
Have you built a text or image search demo with a vector database, but still feel like you have a long way to go to enable a core user flow like natural language search, real-time personalization or retrieval for your shopping assistant? Are you dealing with complex data like job listings, travel destinations or second hand fashion items with 10s of metadata properties? In this workshop we will build a vector search-powered system that can deal with complex data and power highly relevant & well converting natural language search with queries like "vintage sweaters under 200" or "cozy highly rated hotels near manhattan midtown with good wifi". We will personalize these results and build product discovery with a real-time feedback loop using click data. We will learn how a fashion retailer added $15M of incremental revenue using Superlinked's ability to create custom embeddings that fit *all* their 1P data signals.