Build AI agents for e-commerce with ADK + Vector Search
This video discusses creating AI agents for e-commerce using ADK and Vector Search to address challenges like keyword/multimodal searches and item recommendations. It highlights advanced Vector Search practices (multimodal, hybrid, task-type embedding) and demonstrates how AI agents with Vector Search improve ""generative"" recommendations, exemplified by a ""Shopper's Concierge"" demo. This demo, using ADK, Google Search grounding, query generation, and multimodal item curation, finds relevant items based on user intent, moving beyond simple text similarity search. Resources: Vertex AI Vector Search →https://goo.gle/3T5xxK5 Agent Development Kit→https://goo.gle/3RGrB9T Shopper's Concierge demo video→https://goo.gle/4jRbMJb Shopper's Concierge sample notebook→https://goo.gle/4kMkxot Chapters: 0:00 - Intro 0:43 - Introduction to Vector Search & Advanced Practices (Kaz Sato) 1:18 - Typical RAG Scenario for E-commerce 2:56 - Challenges with Basic RAG in E-commerce 8:08 - Vector Search Advanced Practices 15:08 - Building the Shopper's Concierge AI Agent with ADK & Vector Search (Kaz Sato) 8:50 - Challenge: Smart Recommendations 9:50 - Solution: AI Agents + Vector Search 11:13 - Shopper's Concierge Demo 14:58 - Code Implementation Walkthrough 15:02 - Q&A and Resources 15:48 - Why ""Agent as a Tool"" vs. Sub-agent? 16:48 - Getting Started Resources Subscribe to Google for Developers → https://goo.gle/developers Speakers: Sita Lakshmi, Kaz Sato Products Mentioned: Agent Developer Kit (ADK)

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