📚 Unstract: LLM-Driven Unstructured Data Extraction

The direction of Unstract is clear: it focuses on using large language models to extract information from unstructured data and convert it into structured JSON outputs. The project is specifically built for API deployments and ETL (Extract, Transform, Load) pipeline workflows. In the realm of document processing and data engineering, turning PDFs or messy documents into clean data has always been a tedious task. The interesting aspect of Unstract is how it combines LLMs, OCR, and prompt engineering to create a modern Intelligent Document Processing (IDP) pipeline. It even includes an MCP server interface, making it easier to integrate with other AI agents or workflows. The hard part is not getting an LLM to extract data correctly once, but ensuring stable and predictable structured outputs within an engineering pipeline. Unstract is essentially exploring a reliable LLM extraction infrastructure tailored for the modern data stack.