White Paper: Operational Data Layer → https://mdb.link/_fvIURcJl44-paper Video: Why Modern Retail Needs Unified Commerce Now → https://youtu.be/UqytWvvB0pQ?si=7bNVODi_rz1rTLPt Subscribe to MongoDB YouTube→ https://mdb.link/subscribe More resources: Blog: Unified Commerce for Retail Innovation → https://mdb.link/_fvIURcJl44-blog Solution Library: Unified Commerce with Smart Search → https://mdb.link/_fvIURcJl44-solution GitHub Repo: Replicate this demo in your own environment → https://github.com/mongodb-industry-solutions/retail-unified-commerce In this video, we explore how MongoDB transforms fragmented retail data into unified, AI-ready experiences. Learn how search evolves from regex to full-text to semantic and hybrid AI search — all running natively inside your operational database. Discover how Atlas Search, Vector Search, and Hybrid Search help retailers power real-time product discovery and personalized customer experiences. Chapters: 00:00 The problem with modern retail experiences 00:43 Why data fragmentation blocks AI adoption 01:20 What is an Operational Data Layer? 01:37 Demo: Real-time inventory with the Leafy App 02:46 The limitations of Regex for product discovery 03:22 MongoDB Atlas Search: Beyond simple pattern matching 04:48 Understanding Embeddings and Vector Search 05:38 How the search engine works under the hood 06:14 Hybrid Search: Combining Text and Vector 06:53 How Reciprocal Rank Fusion (RRF) works 07:31 Update: Search for Enterprise and Community 07:49 New Feature: Score Fusion vs. RRF Visit Mongodb.com → https://mdb.link/MongoDB Read the MongoDB Blog → https://mdb.link/Blog Read the Developer Blog → https://mdb.link/developerblog

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