A new open-source extraction service has been launched, designed to streamline the process of extracting structured data from unstructured sources using Large Language Models (LLMs). This service builds on the capabilities of the LangChain library and includes a starter repository to assist users in developing their own extraction applications, featuring a web application that can be extended for non-technical users. It addresses the challenges faced by enterprises in extracting valuable insights from varied document types by replacing traditional rule-based and complex ML-based models with LLM-driven solutions, which are easier to maintain and scale. The service employs FastAPI and Postgresql to offer a REST API, enabling the creation of "extractors" that define the schema, prompt, and reference examples for the LLM. It supports MIME-type based parsing of PDFs and HTML files and can be extended to other formats. The service is designed to extract multiple entities from text, allowing for flexibility and scalability in information extraction. Additionally, it offers a practical example of use, demonstrating how to register and invoke an extractor to retrieve structured data from text inputs.