video1.0<iframe src="https://www.loom.com/embed/5f9d9e3ba21443039f8874bf8ff348a8" frameborder="0" width="1920" height="1440" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>14401920Loomhttps://www.loom.com14401920https://cdn.loom.com/sessions/thumbnails/5f9d9e3ba21443039f8874bf8ff348a8-478df72d642cc9d8.gif99.767In this video, I discuss a new pipeline we've built that enhances semantic search for fashion products. It addresses challenges in finding personalized fits through image and text search, ultimately aiming to improve conversion rates. The pipeline uses semantic AI and color detection to find similar products based on user selections. I also mention that this model is trained on an open-source dataset from Kaggle and can be integrated into Shopify stores. Please let me know your thoughts on this approach!