Zilliz Hands-On | Full-Text Search and Vector Search in One Engine - From Hybrid Search to Multimodal Search

🎯 Event OverviewIn this workshop, participants will learn about vector search, hybrid search, and multimodal search using Milvus / Zilliz Cloud, focusing on Japanese data through hands-on experience. Combining Japanese morphological analysis, BM25, dense vectors, and image search, attendees will gain practical experience in building a search infrastructure that considers performance, operational efficiency, and cost. The second half will include a demonstration on transitioning from an existing Milvus environment to Zilliz Cloud and the new features of Milvus 3.0.Even those new to vector databases can participate. We will start together with a free trial registration for Zilliz Cloud on the day of the event. No prior preparation is required; just bring a laptop and a browser.📍 Venue: TKP Tokyo Station Conference Center, Conference Room 1A 〒103-0028 Tokyo, Chuo Ward, Yaesu 1-8-16, Shin Makicho Building, 1-minute walk from JR Tokyo Station Yaesu Chuo Exit📆 Date: September 17, 2026 (Thursday) 18:30–21:20 (Registration starts at 18:00)👥 Format: In-person / Hands-on📝 Capacity: 40 people💻 What to Bring: Laptop (any OS as long as the browser works)🍴 Snacks and Drinks: Pizza, light snacks, and drinks will be provided.📅 Agenda18:00-18:30 | Registration18:30-19:00 | Session: Operating a Vector Search Infrastructure in Production - Real Solutions for Performance, Cost, and Migration19:00-19:10 | Demo A: Beyond the Hands-On - Full-Scale Japanese Hybrid Search19:10-20:30 | Hands-on20:30-20:40 | Q&A20:40-20:50 | Demo B: Transitioning from Self-Hosted Milvus to Zilliz Cloud - A Hands-On Experience20:40-20:50 | Demo C: Searching While Storing in a Data Lake - Milvus 3.0 External Collections20:50-21:20 | Open NetworkingInstructorYan Yulan / Zilliz Founding Solution Architect, PhDRecommended forHands-On Content (Approx. 80 minutes)On Zilliz Cloud, participants will build a Japanese document search from scratch. This will be conducted based on Milvus 2.6.Lab Content TimeLab 0 Environment Setup - Connection Check to Zilliz Cloud Approx. 15 minutesLab 1 Japanese Semantic Search - From Collection Creation to Data Ingestion and Search Approx. 15 minutesLab 2 Japanese Word Segmentation and Full-Text Search, and Hybrid Search Approx. 20 minutesLab 3 Multimodal Search - Retrieving Document Pages with Charts Using Japanese Queries Approx. 20 minutesLab 4 (Optional) Advanced Search Usable with a Single Added Line Approx. 10 minutesNote: Lab 4 is optional. Even if you do not finish it on the day, you will be able to take the notebook home and try it out in your own environment later.Session (30 minutes)Operating a Vector Search Infrastructure in Production - Real Solutions for Performance, Cost, and MigrationThis session will provide insights for those considering vector search and those who already operate it.Vector search has become easier up to the Point of Proof of Concept (PoC). The challenge lies beyond that. As data increases, updates do not stop, and tuning indexes and invoices become problems simultaneously - many projects stall at this point.In this session, Zilliz, the developer of Milvus, will discuss how it has approached these challenges. We will cover performance on large datasets with the search engine Cardinal, automation of tuning with AUTOINDEX, cost structures through hierarchical storage and quantization, and operations and security including BYOC. We will also specifically present domestic and international implementation examples and transitions from self-hosted environments.Lastly, we will briefly touch on the direction Milvus 3.0, which was released last month, is heading.DemoDemo A: Beyond the Hands-On - Full-Scale Japanese Hybrid SearchDemo B: Transitioning from Self-Hosted Milvus to Zilliz Cloud - A Hands-On ExperienceDemo C: Searching While Storing in a Data Lake - Milvus 3.0 External CollectionsAbout ZillizZilliz is a company that provides infrastructure for unstructured data for AI, and develops the open-source vector database Milvus. As a pioneer in the field of Vector Database and Vector Lakebase, Zilliz assists in transforming large-scale unstructured data such as text, images, audio, video, code, logs, and user behaviors into intelligent assets that AI can search, analyze, govern, and utilize.Zilliz Official Website⚠️ Notes📩 Inquiries 📧 [email protected]