AI Webinar - Building an AI-Ready Data Backbone

Webinar I gave with AI Camp and Aiven on AI-ready data backbone, and specifically how OpenSearch unlocks AI-powered search and log analytics: https://www.aicamp.ai/event/eventdetails/W2026032610 Blog post: https://dmitry-kan.medium.com/webinar-building-an-ai-ready-data-backbone-with-aiven-google-cloud-4629f97f69bd LLM/RAG/AI Agents course: https://dmitry-kan.medium.com/course-large-language-models-and-generative-ai-for-nlp-2025-98e31780de30 Free tier OpenSearch: https://aiven.io/free-opensearch Time codes: 1:01 Dima's intro + Vector Podcast 4:56 About Aiven 7:06 Why best? - Question from the audience 10:22 Free Tier OpenSearch! 11:57 Aiven's unifed platform 12:58 OpenSearch: What and Why 17:00 Why OpenSearch is AI-Ready? 18:26 What Aiven's OpenSearch gives you 20:44 Lexical vs semantic search 22:51 Technical use cases of OpenSearch 24:17 Reference Architecture with Kafka as event processor, and OpenSearch as storage and search layer 25:37 Aiven's case studies for OpenSearch 26:27 When to choose OpenSearch? 28:21 Demo of OpenSearch query UI 32:12 Is there any advantage in using Qdrant over OpenSearch? - Question from the audience 34:30 What is the vector lenght (in this demo)? - Question from the audience 36:27 What are the main advantages of Aiven's OpenSearch compared to Elasticsearch? - Question from the audience 32:11 Demo of Search Relevancy Workbench: visual way of searching Show notes: - User Behaviour Insights: https://www.ubisearch.dev/ - Webinar's demo code part 1: Episode download / transcribe / index: https://github.com/dimakan-dev/conduit-transcripts/blob/main/DATA_PROCESSING_GUIDE.md - Webinar's demo code part 2: Main UI and quality dashboards: https://github.com/dimakan-dev/preparing-data-for-opensearch-and-rag/blob/main/workshop/STREAMLIT_README.md