Staging environment
Free Lesson

Optimizing Multimodal Vector Search for E-commerce

60 min
Feb 13, 2026 1:30 PM
Virtual (Zoom)

In this video

What you'll learn

Using visual evals to benchmark embedding quality

We’ll walk through how to perform comparative evals and visualize the quality of embeddings for your queries and dataset

Vector search without a performance hit… is that possible?

Embedding generation takes time and holds back the entire search stack. How can you make it fast?

How to test and roll out embeddings to production

We’ll show you how real ecommerce companies actually roll out vector search to avoid operational risk and max out KPIs.

Why this topic matters

Performance lags or poor search results can derail vector search implementations. Inspired by successful large-scale deployments, this session will teach you how to avoid pitfalls and get your vector search into production with the best outcome. Not all embedding models are created equal. You’ll learn how to integrate high quality embeddings for improved search quality at little performance cost

You'll learn from

Philippe Bouzaglou

Philippe Bouzaglou

Technical Founder at Vectra, the AI foundation model for e-commerce search

Trey Grainger

Trey Grainger

Founder @ Searchkernel, Author of "AI-Powered Search"

Vectra

Harvard University
Searchkernel
Gorillas
Lucidworks
CareerBuilder
See all products from AI-Powered Search