AI Knowledge Bases at Scale: Discovering Key Analytics Insights in Massive Data Archives

You’ll see how to semantically search across a large-scale real-world dataset — and how MindsDB agents can dynamically generate queries to surface insights from the Knowledge Base. The session demonstrates MindsDB’s scalability, metadata-aware querying, and end-to-end integration of Knowledge Bases with natural-language reasoning.

Why watch

Most “RAG” demos crumble at real-world scale. In this live, hands-on session, Andriy Burkov shows how to build a production-grade Knowledge Base in MindsDB on top of a massive real-world dataset — then wire up an agent that generates targeted KB queries on demand to deliver fast, grounded, source-linked answers at scale.

What you’ll learn

• Load and organize a multi-million-article dataset into a MindsDB Knowledge Base designed for speed, recall, and verifiability.
• Structure and execute dynamic KB queries that pull exactly the facts you need.
• Practical tips for grounding, evaluation, and latency at the millions-of-facts scale.

Who should watch

Data and ML engineers, analytics leaders, AI product builders, enterprise architects — anyone who needs trustworthy answers from large corporate text archives, not just summaries.