Tevian Publishes a Habr Article on Multimodal Models in E‑commerce

We published a new article on Habr, “How Multimodal Models Learned to Understand Products, Not Just Images.”

The article explores how visual search and image-based product search technologies have evolved in e‑commerce: from computer vision models and CLIP to multimodal models that combine images, text descriptions, and product card attributes into a unified product representation.

From Visual Search to Product Understanding

We explain why visual similarity alone is not enough for accurate SKU-level search, how models work with multiple images of the same product and noisy catalog data, and why modern product understanding systems need both textual and visual features.

We also look at the evolution of multimodal approaches through e-CLIP, MOON, MOON2.0, AFMRL, and MOON3.0, and how they address fine-grained product understanding — distinguishing visually similar products based on detailed attributes.

Read the article on Habr