Manual resume screening poses significant challenges for HR professionals due to the sheer volume of applications and the diverse formats of resumes. Traditional parsing solutions often struggle with non-standard layouts and fail to produce structured data from unstructured text. The article introduces Ragie, a fully managed RAG-as-a-service platform, which uses entity extraction to address these issues by understanding document semantics and providing consistently structured outputs. A tutorial within the article demonstrates how to develop a resume parser application using Ragie's API to extract data like personal information, skills, experience, and education from various resume formats. It outlines the necessary project setup, including environment configuration, creating extraction schemas, and handling document processing workflows. Additionally, it describes building a Streamlit-based web interface for uploading resumes and displaying results, emphasizing Ragie's flexibility and intelligence compared to traditional parsers. The article suggests potential expansions, such as capturing more detailed candidate information, to enhance the application's capabilities further.