Agents
Agentic Reasoning in Practice: Making Sense of Structured and Unstructured Data
Databricks explores how agentic AI systems can reason over both structured data (such as tables and databases) and unstructured data (such as documents and text) to answer complex business questions.
Databricks explores how agentic AI systems can reason over both structured data (such as tables and databases) and unstructured data (such as documents and text) to answer complex business questions. The post likely covers architectural patterns and tools—such as Mosaic AI and the Databricks Data Intelligence Platform—that enable agents to autonomously plan, retrieve, and synthesize information across heterogeneous data sources. It addresses practical implementation considerations for building reliable, production-ready agentic pipelines that combine SQL-based structured querying with retrieval-augmented generation (RAG) for unstructured content.
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Source: Databricks | 2026-04-14