AI Webinar - Building an AI-Ready Data Backbone

About this episode

Dmitry Kan discusses building an AI-ready data backbone and the capabilities of OpenSearch in AI-powered search and log analytics.

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)…

People in this episode

Host: Dmitry Kan

Topics covered

• AI-ready data backbone
• OpenSearch
• AI-powered search
• log analytics
• data architecture
• search relevancy

Keywords

• AI
• OpenSearch
• Aiven
• data backbone
• log analytics
• search
• architecture
• Qdrant
• Elasticsearch

Mentioned in this episode

Organizations: AI Camp, Aiven, OpenSearch, Google Cloud, Elasticsearch, Qdrant

Books & works: Webinar, Blog post, LLM/RAG/AI Agents course, User Behaviour Insights

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