Danica Fine - Donut Kill My Vibe: Enriching RAG with Apache Iceberg™ for Sweet, Structured Retrieval

Danica began her career as a software engineer and pivoted to developer relations, where she focussed primarily on open source technologies under the Apache Software Foundation umbrella such as Apache Kafka and Apache Flink. She now leads the open source advocacy efforts at Snowflake, supporting Apache Iceberg and Apache Polaris (incubating).

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Donut Kill My Vibe: Enriching RAG with Apache Iceberg™ for Sweet, Structured Retrieval

Unstructured text powers most Retrieval-Augmented Generation (RAG) systems. But when users want something specific, structure matters. See how Apache Iceberg™ can add high-performance, queryable structure to a RAG stack, enabling more accurate, personalized, and grounded responses.

Enter: DonutBot, an AI assistant that maps free-form donut orders—“something sweet and seasonal with sprinkles, <400 calories”—to real items. DonutBot combines semantic vector search over product descriptions with structured filters from Iceberg tables that serve as the donut metadata source of truth. This powers hybrid search that blends fuzzy LLM reasoning with precise constraints. We then use TruLens to evaluate the system, showing gains in groundedness and context relevance, yielding fewer hallucinations and better, data-backed recommendations.

Whether you're building AI for snacks or enterprise search, this talk shows how Iceberg brings structured intelligence to your RAG stack—one donut at a time.