[Demo] Use Agent Bricks to quickly build a production AI agent that transforms unlabeled text documents into a structured table with extracted information. With built-in feedback loops and AI-assisted evaluation, the Information Extraction agent continuously improves, accelerating automation while reducing risk and effort. See how easy it is to build in this demo: https://lnkd.in/gAd7buCB
This is pretty impressive. Setting up schemas and attribute definition on unstructured datasets is still a very hard problem to solve
Impressive! Turning unstructured text into structured, usable data has always been a challenge. Agent Bricks seems to make it seamless.
This is one small demo using agentbricks https://medium.com/@bijumathewt/databricks-agent-bricks-automating-invoice-data-extraction-from-pdf-e47167c6bae9
Principal Data Architect | Agentic AI & LLM Ops | Databricks Lakehouse • Azure • Spark/Delta | Lineage & compliance by design
3dAgent Bricks is the bridge to reliable document intelligence—schema-first extraction, continuous improvement, and quality you can measure. A real step toward agents that actually ship.