AI is revolutionizing information retrieval by simplifying the extraction of valuable data from unstructured documents, using tools like Guardrails to enhance accuracy and efficiency. Traditional methods required extensive programming to train machine learning models, while AI engines, equipped with Large Language Models (LLMs), offer a more adaptable solution. Guardrails facilitates this by automating quality control, using specifications to ensure AI outputs meet expected formats and handling necessary re-prompts. This process is illustrated through a Python application that extracts key details from a credit card agreement, highlighting how Guardrails uses Pydantic to define output parameters and employs OpenAI's GPT-4 for processing. The system ensures the AI response aligns with the predefined format, correcting and validating outputs as needed, thereby transforming unstructured data into structured formats like JSON. This approach unlocks significant applications in sectors such as finance and healthcare, making complex information retrieval more accessible and cost-effective.