Optimize Structured Data Retrieval With Evals

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Optimize Structured Data Retrieval With Evals

Hosted by Daniel Svonava and Hamel Husain

Fri, May 9, 2025

12:00 AM UTC (45 minutes)

Virtual (Zoom)

Free to join

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189 students

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AI Evals For Engineers & PMs

Hamel Husain and Shreya Shankar

View syllabus

Fri, May 9, 2025

12:00 AM UTC (45 minutes)

Virtual (Zoom)

Free to join

189 students

Invite your network

Go deeper with a course

AI Evals For Engineers & PMs

Hamel Husain and Shreya Shankar

View syllabus

What you'll learn

Identify blind spots in your current evals.

Understand how hybrid search, boosts, filters and reranks on structured fields shape your results in unexpected ways.

Build search evals that account for semi-structured data

Most real world data has structure. Learn how to properly account for this when writing evals.

Build more realistic evaluation datasets

Learn practical techniques for creating on enhancing datasets with web scraping and LLM judges in clever ways.

Why this topic matters

It’s time to stop evaluating on queries like “hotel nyc” while your users search “top family friendly hotel near manhattan midtown under 200”! Daniel will share his experience evaluating retrieval quality across multiple domains (travel, jobs, fashion). Take your evals beyond text-on-text matching and close the gap between your evals and production.

You'll learn from

Daniel Svonava

CEO at Superlinked. Previously ML TL at YouTube.

Daniel is the CEO & co-founder of Superlinked.com, an open source framework and 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/year-worth of ads.

Hamel Husain

ML Engineer with 20 years of experience

Hamel is a machine learning engineer with over 20 years of experience. He has worked with innovative companies such as Airbnb and GitHub, which included early LLM research used by OpenAI, for code understanding. He has also led and contributed to numerous popular open-source machine-learning tools. Hamel is currently an independent consultant helping companies build AI products.

Previously at