When users can’t describe what they want, they show it. Image search has emerged as a powerful way to capture user intent in e-commerce. But building a system that is accurate, fast, merch oriented and cost-effective at industrial scale is no easy feat.

In this talk, we’ll share how the Search & Publication team at Adeo (Leroy Merlin group) built a scalable hybrid image search engine serving over 10 million products, combining visual embeddings, textual signals, and knowledge-graph-enhanced metadata.

We will share with you:

• How we built a hybrid architecture combining image embeddings and LLM based lexical search, backed by our Knowledge Graph.

• Our journey into vector quantization techniques (bf16, int8, int4, int2, BBQ in Elasticsearch), and how they impacted latency, precision and cost trade-offs.